{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Demo of 2019-nCov Data Analysis\n",
    "\n",
    "The novel coronavirus (2019-nCov) has recently swept through China and triggered a global health emergency.  In order to better assess the situation, we need to analyze the epidemic data.  Many websites have been publishing this in real time, for example, [Ding Xiang Yuan](https://ncov.dxy.cn/ncovh5/view/pneumonia), [Tencent](https://news.qq.com/zt2020/page/feiyan.htm), [John Hopkins](https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6), etc.  These websites provides timely information for the general public, but they fall short of providing sufficient data for analysis.  For example, answering any of the following simple questions will be very difficult or impossible by using the websites mentioned above:\n",
    "\n",
    "* What is the number of confirmed cases in the past 10 days in the Hubei Province ?\n",
    "* How do the daily new confirmed cases compare between the provinces of Guangdong and Zhejiang ?\n",
    "* Which city have the second highest fatality rates ?  \n",
    "* (And much more ...)\n",
    "\n",
    "In order to be able to analyze the data, a better and more convenient data set is necessary.  The [DXY-2019-nCoV-Data](https://github.com/BlankerL/DXY-2019-nCoV-Data) GitHub project  constantly snaps the real time epidemic report from  [Ding Xiang Yuan](https://ncov.dxy.cn/ncovh5/view/pneumonia), and saves it into a CSV file.  However, this CSV file is still inconvenient for general users, because different cities reports at different times, and the reporting format changes from time to time.\n",
    "\n",
    "Therefore, this project [nCov2019_analysis](https://github.com/jianxu305/nCov2019_analysis) is created.  Its main purpose are the following:\n",
    "\n",
    "1. Performs essential data cleanings\n",
    "2. Provides a convenient structured data for users to explore\n",
    "3. Using this data set, analyze some aspects of this epidemic\n",
    "\n",
    "Following is a demo of the basic usage:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import utils   # some convenient functions\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Obtain Raw CSV Data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last update:  2020-05-08 20:39:48\n",
      "Data date range:  2020-01-22 to 2020-05-08\n",
      "Number of rows in raw data:  165536\n"
     ]
    }
   ],
   "source": [
    "data = utils.load_chinese_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>continentName</th>\n",
       "      <th>continentEnglishName</th>\n",
       "      <th>countryName</th>\n",
       "      <th>countryEnglishName</th>\n",
       "      <th>province_name</th>\n",
       "      <th>provinceEnglishName</th>\n",
       "      <th>province_zipCode</th>\n",
       "      <th>province_confirmed</th>\n",
       "      <th>province_suspected</th>\n",
       "      <th>province_cured</th>\n",
       "      <th>province_dead</th>\n",
       "      <th>update_time</th>\n",
       "      <th>city_name</th>\n",
       "      <th>cityEnglishName</th>\n",
       "      <th>city_zipCode</th>\n",
       "      <th>city_confirmed</th>\n",
       "      <th>city_suspected</th>\n",
       "      <th>city_cured</th>\n",
       "      <th>city_dead</th>\n",
       "      <th>update_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>亚洲</td>\n",
       "      <td>Asia</td>\n",
       "      <td>中国</td>\n",
       "      <td>China</td>\n",
       "      <td>台湾</td>\n",
       "      <td>Taiwan</td>\n",
       "      <td>710000</td>\n",
       "      <td>440</td>\n",
       "      <td>348.0</td>\n",
       "      <td>355</td>\n",
       "      <td>6</td>\n",
       "      <td>2020-05-08 20:39:48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-05-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>亚洲</td>\n",
       "      <td>Asia</td>\n",
       "      <td>中国</td>\n",
       "      <td>China</td>\n",
       "      <td>中国</td>\n",
       "      <td>China</td>\n",
       "      <td>951001</td>\n",
       "      <td>84416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>79348</td>\n",
       "      <td>4643</td>\n",
       "      <td>2020-05-08 20:39:48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-05-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>亚洲</td>\n",
       "      <td>Asia</td>\n",
       "      <td>中国</td>\n",
       "      <td>China</td>\n",
       "      <td>香港</td>\n",
       "      <td>Hong Kong</td>\n",
       "      <td>810000</td>\n",
       "      <td>1044</td>\n",
       "      <td>47.0</td>\n",
       "      <td>960</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-05-08 20:38:47</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-05-08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  continentName continentEnglishName countryName countryEnglishName  \\\n",
       "0            亚洲                 Asia          中国              China   \n",
       "1            亚洲                 Asia          中国              China   \n",
       "2            亚洲                 Asia          中国              China   \n",
       "\n",
       "  province_name provinceEnglishName  province_zipCode  province_confirmed  \\\n",
       "0            台湾              Taiwan            710000                 440   \n",
       "1            中国               China            951001               84416   \n",
       "2            香港           Hong Kong            810000                1044   \n",
       "\n",
       "   province_suspected  province_cured  province_dead         update_time  \\\n",
       "0               348.0             355              6 2020-05-08 20:39:48   \n",
       "1                 0.0           79348           4643 2020-05-08 20:39:48   \n",
       "2                47.0             960              4 2020-05-08 20:38:47   \n",
       "\n",
       "  city_name cityEnglishName  city_zipCode  city_confirmed  city_suspected  \\\n",
       "0       NaN             NaN           NaN             NaN             NaN   \n",
       "1       NaN             NaN           NaN             NaN             NaN   \n",
       "2       NaN             NaN           NaN             NaN             NaN   \n",
       "\n",
       "   city_cured  city_dead update_date  \n",
       "0         NaN        NaN  2020-05-08  \n",
       "1         NaN        NaN  2020-05-08  \n",
       "2         NaN        NaN  2020-05-08  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(3)  # Check the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Data Processing\n",
    "This step does the the following:\n",
    "* Aggregate the raw CSV data into daily data\n",
    "* Perform basic cleaning due to inconsistent reporting schemes.  For example, the same city may appear as different names at different reporting time, etc\n",
    "* Added daily new confirmed / cured / dead numbers\n",
    "* Added *_en* columns for *province_name* and *city_name* so that non-Chinese users can easily use the dataset \n",
    "\n",
    "The resulting dataset is a flat Pandas data frame, logically indexed by (update_date, province_name(_en), city_name(_en)), so users can easily slice the data in whatever way they want, or export to other applications."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "daily_frm = utils.aggDaily(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>update_date</th>\n",
       "      <th>continentName</th>\n",
       "      <th>countryName</th>\n",
       "      <th>continentEnglishName</th>\n",
       "      <th>countryEnglishName</th>\n",
       "      <th>province_name</th>\n",
       "      <th>province_name_en</th>\n",
       "      <th>city_name</th>\n",
       "      <th>city_name_en</th>\n",
       "      <th>zip_code</th>\n",
       "      <th>cum_confirmed</th>\n",
       "      <th>cum_cured</th>\n",
       "      <th>cum_dead</th>\n",
       "      <th>new_confirmed</th>\n",
       "      <th>new_cured</th>\n",
       "      <th>new_dead</th>\n",
       "      <th>update_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>329</th>\n",
       "      <td>2020-05-08</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>Heilongjiang</td>\n",
       "      <td>鹤岗</td>\n",
       "      <td>Hegang</td>\n",
       "      <td>230400.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-05-08 08:23:52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>2020-05-08</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>Heilongjiang</td>\n",
       "      <td>黑河</td>\n",
       "      <td>Heihe</td>\n",
       "      <td>231100.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-05-08 08:23:52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>324</th>\n",
       "      <td>2020-05-08</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>Heilongjiang</td>\n",
       "      <td>齐齐哈尔</td>\n",
       "      <td>Qiqihaer</td>\n",
       "      <td>230200.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-05-08 08:23:52</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    update_date continentName countryName continentEnglishName  \\\n",
       "329  2020-05-08            亚洲          中国                 Asia   \n",
       "328  2020-05-08            亚洲          中国                 Asia   \n",
       "324  2020-05-08            亚洲          中国                 Asia   \n",
       "\n",
       "    countryEnglishName province_name province_name_en city_name city_name_en  \\\n",
       "329              China          黑龙江省     Heilongjiang        鹤岗       Hegang   \n",
       "328              China          黑龙江省     Heilongjiang        黑河        Heihe   \n",
       "324              China          黑龙江省     Heilongjiang      齐齐哈尔     Qiqihaer   \n",
       "\n",
       "     zip_code  cum_confirmed  cum_cured  cum_dead  new_confirmed  new_cured  \\\n",
       "329  230400.0            5.0        5.0       0.0            0.0        0.0   \n",
       "328  231100.0           14.0       14.0       0.0            0.0        0.0   \n",
       "324  230200.0           43.0       42.0       1.0            0.0        0.0   \n",
       "\n",
       "     new_dead         update_time  \n",
       "329       0.0 2020-05-08 08:23:52  \n",
       "328       0.0 2020-05-08 08:23:52  \n",
       "324       0.0 2020-05-08 08:23:52  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily_frm.tail(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Data Exploration Examples"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1 Slicing Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Selecting a province by its English (Pinyin) name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>update_date</th>\n",
       "      <th>continentName</th>\n",
       "      <th>countryName</th>\n",
       "      <th>continentEnglishName</th>\n",
       "      <th>countryEnglishName</th>\n",
       "      <th>province_name</th>\n",
       "      <th>province_name_en</th>\n",
       "      <th>city_name</th>\n",
       "      <th>city_name_en</th>\n",
       "      <th>zip_code</th>\n",
       "      <th>cum_confirmed</th>\n",
       "      <th>cum_cured</th>\n",
       "      <th>cum_dead</th>\n",
       "      <th>new_confirmed</th>\n",
       "      <th>new_cured</th>\n",
       "      <th>new_dead</th>\n",
       "      <th>update_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>164411</th>\n",
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       "      <td>Zhongshan</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>亚洲</td>\n",
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       "      <td>China</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>佛山</td>\n",
       "      <td>Foshan</td>\n",
       "      <td>440600.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>亚洲</td>\n",
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       "      <td>China</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>广州</td>\n",
       "      <td>Guangzhou</td>\n",
       "      <td>440100.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-01-24 23:35:03</td>\n",
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       "    <tr>\n",
       "      <th>164407</th>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>惠州</td>\n",
       "      <td>Huizhou</td>\n",
       "      <td>441300.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-01-24 23:35:03</td>\n",
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       "    <tr>\n",
       "      <th>164403</th>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>深圳</td>\n",
       "      <td>Shenzhen</td>\n",
       "      <td>440300.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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      "text/plain": [
       "       update_date continentName countryName continentEnglishName  \\\n",
       "164411  2020-01-24            亚洲          中国                 Asia   \n",
       "164405  2020-01-24            亚洲          中国                 Asia   \n",
       "164406  2020-01-24            亚洲          中国                 Asia   \n",
       "164407  2020-01-24            亚洲          中国                 Asia   \n",
       "164403  2020-01-24            亚洲          中国                 Asia   \n",
       "\n",
       "       countryEnglishName province_name province_name_en city_name  \\\n",
       "164411              China           广东省        Guangdong        中山   \n",
       "164405              China           广东省        Guangdong        佛山   \n",
       "164406              China           广东省        Guangdong        广州   \n",
       "164407              China           广东省        Guangdong        惠州   \n",
       "164403              China           广东省        Guangdong        深圳   \n",
       "\n",
       "       city_name_en  zip_code  cum_confirmed  cum_cured  cum_dead  \\\n",
       "164411    Zhongshan  442000.0            2.0        0.0       0.0   \n",
       "164405       Foshan  440600.0            7.0        0.0       0.0   \n",
       "164406    Guangzhou  440100.0            7.0        0.0       0.0   \n",
       "164407      Huizhou  441300.0            5.0        0.0       0.0   \n",
       "164403     Shenzhen  440300.0           15.0        2.0       0.0   \n",
       "\n",
       "        new_confirmed  new_cured  new_dead         update_time  \n",
       "164411            NaN        NaN       NaN 2020-01-24 23:35:03  \n",
       "164405            NaN        NaN       NaN 2020-01-24 23:35:03  \n",
       "164406            NaN        NaN       NaN 2020-01-24 23:35:03  \n",
       "164407            NaN        NaN       NaN 2020-01-24 23:35:03  \n",
       "164403            NaN        NaN       NaN 2020-01-24 23:35:03  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily_frm[daily_frm['province_name_en'] == 'Guangdong'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Selecting a city by its Chinese name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>update_date</th>\n",
       "      <th>continentName</th>\n",
       "      <th>countryName</th>\n",
       "      <th>continentEnglishName</th>\n",
       "      <th>countryEnglishName</th>\n",
       "      <th>province_name</th>\n",
       "      <th>province_name_en</th>\n",
       "      <th>city_name</th>\n",
       "      <th>city_name_en</th>\n",
       "      <th>zip_code</th>\n",
       "      <th>cum_confirmed</th>\n",
       "      <th>cum_cured</th>\n",
       "      <th>cum_dead</th>\n",
       "      <th>new_confirmed</th>\n",
       "      <th>new_cured</th>\n",
       "      <th>new_dead</th>\n",
       "      <th>update_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>164605</th>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>武汉</td>\n",
       "      <td>Wuhan</td>\n",
       "      <td>420100.0</td>\n",
       "      <td>495.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-01-24 17:30:09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163420</th>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>武汉</td>\n",
       "      <td>Wuhan</td>\n",
       "      <td>420100.0</td>\n",
       "      <td>572.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2020-01-25 23:55:35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162795</th>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>武汉</td>\n",
       "      <td>Wuhan</td>\n",
       "      <td>420100.0</td>\n",
       "      <td>618.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-01-26 13:50:35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161611</th>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>武汉</td>\n",
       "      <td>Wuhan</td>\n",
       "      <td>420100.0</td>\n",
       "      <td>698.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2020-01-27 16:42:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160789</th>\n",
       "      <td>2020-01-28</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>武汉</td>\n",
       "      <td>Wuhan</td>\n",
       "      <td>420100.0</td>\n",
       "      <td>1590.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>892.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>2020-01-28 16:36:17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       update_date continentName countryName continentEnglishName  \\\n",
       "164605  2020-01-24            亚洲          中国                 Asia   \n",
       "163420  2020-01-25            亚洲          中国                 Asia   \n",
       "162795  2020-01-26            亚洲          中国                 Asia   \n",
       "161611  2020-01-27            亚洲          中国                 Asia   \n",
       "160789  2020-01-28            亚洲          中国                 Asia   \n",
       "\n",
       "       countryEnglishName province_name province_name_en city_name  \\\n",
       "164605              China           湖北省            Hubei        武汉   \n",
       "163420              China           湖北省            Hubei        武汉   \n",
       "162795              China           湖北省            Hubei        武汉   \n",
       "161611              China           湖北省            Hubei        武汉   \n",
       "160789              China           湖北省            Hubei        武汉   \n",
       "\n",
       "       city_name_en  zip_code  cum_confirmed  cum_cured  cum_dead  \\\n",
       "164605        Wuhan  420100.0          495.0       31.0      23.0   \n",
       "163420        Wuhan  420100.0          572.0       32.0      38.0   \n",
       "162795        Wuhan  420100.0          618.0       40.0      45.0   \n",
       "161611        Wuhan  420100.0          698.0       42.0      63.0   \n",
       "160789        Wuhan  420100.0         1590.0       47.0      85.0   \n",
       "\n",
       "        new_confirmed  new_cured  new_dead         update_time  \n",
       "164605            NaN        NaN       NaN 2020-01-24 17:30:09  \n",
       "163420           77.0        1.0      15.0 2020-01-25 23:55:35  \n",
       "162795           46.0        8.0       7.0 2020-01-26 13:50:35  \n",
       "161611           80.0        2.0      18.0 2020-01-27 16:42:57  \n",
       "160789          892.0        5.0      22.0 2020-01-28 16:36:17  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily_frm[daily_frm['city_name'] == '武汉'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Selecting a date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>update_date</th>\n",
       "      <th>continentName</th>\n",
       "      <th>countryName</th>\n",
       "      <th>continentEnglishName</th>\n",
       "      <th>countryEnglishName</th>\n",
       "      <th>province_name</th>\n",
       "      <th>province_name_en</th>\n",
       "      <th>city_name</th>\n",
       "      <th>city_name_en</th>\n",
       "      <th>zip_code</th>\n",
       "      <th>cum_confirmed</th>\n",
       "      <th>cum_cured</th>\n",
       "      <th>cum_dead</th>\n",
       "      <th>new_confirmed</th>\n",
       "      <th>new_cured</th>\n",
       "      <th>new_dead</th>\n",
       "      <th>update_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>161648</th>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>上海市</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>嘉定区</td>\n",
       "      <td>Jiadingqu</td>\n",
       "      <td>310114.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-01-27 15:56:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161638</th>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>上海市</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>外地来沪人员</td>\n",
       "      <td>Non_Residence</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-01-27 15:56:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161649</th>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>上海市</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>奉贤区</td>\n",
       "      <td>Fengxian</td>\n",
       "      <td>310120.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-01-27 15:56:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161647</th>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>上海市</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>宝山区</td>\n",
       "      <td>Baoshanqu</td>\n",
       "      <td>310113.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-01-27 15:56:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161642</th>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>亚洲</td>\n",
       "      <td>中国</td>\n",
       "      <td>Asia</td>\n",
       "      <td>China</td>\n",
       "      <td>上海市</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>徐汇区</td>\n",
       "      <td>Xuhuiqu</td>\n",
       "      <td>310104.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-01-27 15:56:40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       update_date continentName countryName continentEnglishName  \\\n",
       "161648  2020-01-27            亚洲          中国                 Asia   \n",
       "161638  2020-01-27            亚洲          中国                 Asia   \n",
       "161649  2020-01-27            亚洲          中国                 Asia   \n",
       "161647  2020-01-27            亚洲          中国                 Asia   \n",
       "161642  2020-01-27            亚洲          中国                 Asia   \n",
       "\n",
       "       countryEnglishName province_name province_name_en city_name  \\\n",
       "161648              China           上海市         Shanghai       嘉定区   \n",
       "161638              China           上海市         Shanghai    外地来沪人员   \n",
       "161649              China           上海市         Shanghai       奉贤区   \n",
       "161647              China           上海市         Shanghai       宝山区   \n",
       "161642              China           上海市         Shanghai       徐汇区   \n",
       "\n",
       "         city_name_en  zip_code  cum_confirmed  cum_cured  cum_dead  \\\n",
       "161648      Jiadingqu  310114.0            1.0        0.0       0.0   \n",
       "161638  Non_Residence      -1.0           23.0        3.0       0.0   \n",
       "161649       Fengxian  310120.0            1.0        0.0       0.0   \n",
       "161647      Baoshanqu  310113.0            1.0        0.0       0.0   \n",
       "161642        Xuhuiqu  310104.0            3.0        0.0       0.0   \n",
       "\n",
       "        new_confirmed  new_cured  new_dead         update_time  \n",
       "161648            1.0        0.0       0.0 2020-01-27 15:56:40  \n",
       "161638           23.0        3.0       0.0 2020-01-27 15:56:40  \n",
       "161649            1.0        0.0       0.0 2020-01-27 15:56:40  \n",
       "161647            1.0        0.0       0.0 2020-01-27 15:56:40  \n",
       "161642            3.0        0.0       0.0 2020-01-27 15:56:40  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily_frm[daily_frm['update_date'] == pd.to_datetime('2020-01-27')].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 Plotting\n",
    "Two convenience plotting functions are provided for basic analysis\n",
    "* Time series plot: *utils.tsplot_conf_dead_cured()* \n",
    "* Cross-sectional plot: *utils.cross_sectional_bar()*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Time series plot examples:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x720 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = utils.tsplot_conf_dead_cured(daily_frm, title='Total Confirmed, Dead, and Cured Counts')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### It's easy to do the same time series plot for a given province"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x720 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "province = 'Henan'   \n",
    "fig = utils.tsplot_conf_dead_cured(daily_frm[daily_frm['province_name_en'] == province],\n",
    "                                  title='Confirmed, Dead, and Cured Counts in ' + province + ' Province')\n",
    "plt.show()                                  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The same thing can be done for a given city.  And you can also use *logy=True* to plot in log scale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SEUmcmdVy921mZkT/jpQc91Tc3ak4oSsuK24R2ErUypAZO44n7JPp7ltCS84Woq5N+wAbiaZH30iUvGSGL2r7hHr7hNMlPVYjxLUt9nWEROlZd6/S62SZWZ0S72FtorWBengS6ybFXq941y7ZOCqTRdOAm5dYDy2J/dMW++6kej0SPEdtos9Xcde7DGBrWZ/tdAg/ZmwL70ct2D5OLZljWMz7WWVem4jUDEqqRETiMLPfA+95tIBptRG6uf2Pu+ekOxYREZG9hZIqEZESzOw0ovWbElrstaqwaBHVru6em+5YRERE9iZKqkRERERERFKg2f9ERERERERSoKRKREREREQkBUqqREREREREUqCkSkREREREJAVKqkRERERERFKgpEpERERERCQFSqpERERERERSoKRKREREREQkBUqqREREREREUqCkSkREREREJAVKqkRERERERFKgpEpERERERCQFSqpERERERERSoKRKREREREQkBUqqREREREREUqCkSkREREREJAVKqkRERERERFKgpEpERERERCQFSqpERERERERSoKRKREREREQkBUqqREREREREUqCkSkREREREJAVKqkRERERERFKgpEpERERERCQFSqpERERERERSoKRKREREREQkBUqqREREREREUqCkSkREREREJAVKqkRERERERFKgpEpERERERCQFSqpERERERERSoKRKREREREQkBUqqREREREREUqCkSkREREREJAVKqkRERERERFKgpEpERERERCQFSqpERERERERSoKRKREREREQkBUqqREREREREUqCkSkREREREJAVKqkRERERERFKgpEpERERERCQFSqpERERERERSoKRKREREREQkBUqqREREREREUqCkSkREREREJAVKqkRERERERFKgpEpERERERCQFSqpERERERERSoKRKREREREQkBUqqREREREREUqCkSkREREREJAVKqkRERERERFKgpEpERERERCQFSqpERERERKTCmdkYM1tlZh/E2Xa9mbmZNYspu9nMlpjZR2Z2akz50WaWH7bdb2YWyuuY2fOhfI6ZZVXG6wLIrKwTVVW1atXyevXqpTuMKm/btm3UqqUcvCbQtaw4em9rFl3PmkPXsmbR9ayaNmzY4O5e1oV5AngQeCq20MxaAycDK2LKOgIDgMOBA4F/m9kh7l4EjASygbeBV4G+wGvAMOBbdz/YzAYAdwK/TP3VlW2vT6rq1avH+vXr0x1GlZeXl0fv3r3THYbsAbqWFUfvbc2i61lz6FrWLLqeVZOZFZZVx91n7Kb1aARwAzA5pqwf8Jy7bwKWmtkSoLuZLQP2dfe3wnmfAvoTJVX9gFvD/i8CD5qZubuX5zUlQ2m+iIiIiIikKtPM5sXcshPZyczOBD539/dLbGoJfBbzfGUoaxkelyzfaR933wp8D+yX9Csph72+pUpERERERFK21d27JbODmdUHhgOnxNscp8xLKS9tnwqnlioREREREUmH9kA74P3Qra8V8K6Z/ZioBap1TN1WwBehvFWccmL3MbNMoDHwTQXGv51aquLYsmULK1euZOPGjekOpcpo3LgxixcvTncYCalbty6tWrWidu3a6Q5FRERERHbD3fOBA4qfh8Sqm7uvMbMpwDNmdg/RRBUdgLnuXmRma82sBzAHGAI8EA4xBbgQeAs4F3izMsZTgZKquFauXEmjRo3IysoizNC411u7di2NGjVKdxhlcncKCgpYuXIl7dq1S3c4IiIiIhKY2bNAb6CZma0EbnH3x+LVdfeFZjYOWARsBa4MM/8BXE40k2A9ogkqXgvljwFPh0ktviGaPbBSKKmKY+PGjUqoqikzY7/99mP16tXpDkVEREREYrj7BWVszyrxPAfIiVNvHtApTvlG4LzUoiwfjanaDSVU1ZeunYiIiIhUJiVVIiIiIiJVRG5uLllZWdSqVYusrCxyc3PTHZIkQN3/RERERESqgNzcXLKzs9mwYQMAy5cvJzs7Wu5p4MCB6QxNyqCWqj1AvyjAhx9+SNeuXTnyyCP55JNP6NmzZ6Wct3fv3sybN69SziUiIiJSUbZs2cLvfve77QlVsQ0bNjB8+PA0RSWJUktVivSLQmTSpEn069eP2267DYDZs2fvUqeoqIiMjIzKDk1ERESquJdeSrxufv5+rF2beP0zzkg+nsq0bNkyHn30UcaMGbPbibZWrFhRyVFJspRUleGaa65h/vz5u93+9ttvs2nTpp3KNmzYwLBhwxg9enTcfbp27cq9995b5rmfeuop7rrrLsyMLl26kJGRwS9+8QvOPfdcABo2bMi6devIy8vjlltuoXnz5syfP5+zzz6bzp07c99991FYWMikSZNo37593HN8/fXXXHbZZXz66acAjBw5kp49e3LPPfcwZswYAH79618zbNgwli1bxmmnncZxxx3H7NmzadmyJZMnT2batGnce++9ZGRkMGPGDKZNm7ZTbLfddhstWrRg/vz5vPrqq/Tt25fjjjuOt99+myOOOIKhQ4dyyy23sGrVKnJzc+nevTvr16/nt7/9Lfn5+WzdupVbb72Vfv36UVhYyNChQ1m0aBGHHXYYhYWFZb6PIiIiIlXJli1beOmllxg1ahSvv/46ZsZpp53G3Llz4yZWbdq0SUOUkgwlVSkqmVCVVZ6ohQsXkpOTw6xZs2jWrBnffPMN11577W7rv//++yxevJimTZty0EEH8etf/5q5c+dy33338cADD+w2ibvqqqs44YQTmDhxIkVFRaxbt4533nmHxx9/nDlz5uDu/PSnP6Vbt260atWKjz/+mGeffZbRo0dz/vnnM378eAYNGsRll11Gw4YNuf7663c5x9y5c/nggw9o164dy5YtY8mSJbzwwguMGjWKY445hmeeeYaZM2cyZcoU/vrXvzJp0iRycnL42c9+xpgxY/juu+/o3r07J510Eo888gj169dnwYIFLFiwgKOOOiql91lERESksixdunR7q9RXX31Fy5Yt+dOf/sTFF19MmzZtdukBBVC/fn1ycnaZVVyqGCVVZSirRSkrK4vly5fvUt62bVvy8vLKfd4333yTc889l2bNmgHQtGnTUusfc8wxtGjRAoD27dtzyimnANC5c2emTZtW6nmeeuopADIyMmjcuDEzZ87krLPOokGDBgCcffbZzJ49m/PPP5927drRtWtXAI4++miWLVtW5mvp3r37TgvxtmvXjs6dOwNw+OGH06dPH8yMzp07bz/e66+/zpQpU7jrrruAaO2wFStWMGPGDK666ioAunTpQpcuXco8v4iIiEi6bNmyhSlTpmxvlapVqxann346l156KX379iUzc8fX8eKhI8OHD2fFihW0adOGnJycvWpISXWlpCpFOTk5FfKLgrvvst5SZmYm27Zt27598+bN27fVqVNn++NatWptf16rVi22bt2a9Ll3J/Y8GRkZCXW/K07OkonV3Rk/fjyHHnroLsfTOlQiIiJS1X366aeMHj2axx9/nK+//ppWrVpx6623cvHFF9O6devd7jdw4EAlUdWQZv9L0cCBAxk1ahRt27bFzGjbti2jRo1K+cPQp08fxo0bR0FBAQDffPMNWVlZvPPOOwBMnjyZLVu2pBx/nz59GDlyJBBNJPHDDz9w/PHHM2nSJDZs2MD69euZOHFipc3mV+zUU0/lgQce2J7gvffeewAcf/zx22dX/OCDD1iwYEGlxiUiIiKyO5s3b+bFF1/klFNOoX379vztb3/jpz/9KS+//DLLli3jlltuKTWhkupLLVV7QEX8onD44YczfPhwTjjhBDIyMjjyyCO588476devH927d6dPnz67tACVx3333Ud2djaPPfYYGRkZjBw5kmOPPZaLLrqI7t27A9FEFUccccT2BK8y/PGPf+Saa66hS5cuuDtZWVm8/PLLXH755QwdOpQuXbrQtWvX7TGKiIiIpMuSJUt49NFHefzxx1m1ahWtW7fmtttu4+KLL6ZVq1bpDk8qgZXW1Wtv0KBBA1+/fv1OZYsXL+awww5LU0RV09q1a2nUqFG6w0iYruHu5eXl0bt373SHUSPpva1ZdD1rDl3Lqi+5KdXzt4/NTkRFTam+efNmJk+ezCOPPMLUqVO3z9KcnZ3NqaeeutctI2NmG9w99V/8qyl1/xMRERERiSM3N5esrCxq1apFVlYWubm5LFmyhBtvvJFWrVpx/vnn8/HHH3P77bezfPlyJk2axOmnn77XJVSi7n97jZycHF544YWdys477zyt0C0iIiISR8npzZcvX86QIUPYtm0bGRkZnHHGGWRnZ3PKKacoiRIlVbsTb/a96mz48OF7TQK1t3dpFRERkdQNHz58p9mdAbZt20bjxo1ZtGgRBx54YJoik6pI3f/iqFu3LgUFBfpyXg25OwUFBdStWzfdoYiIiEg1tmLFirjlP/zwgxIq2YVaquJo1aoVK1euZPXq1ekOpcrYuHFjtUlU6tatq5l2REREpFxWrVrFddddt9sf19u0aVPJEUl1oKQqjtq1a9OuXbt0h1Gl5OXlceSRR6Y7DBEREZEKsW3bNsaMGcMNN9zAunXr6N+/P//6178oLCzcXqd+/frk5OSkMUqpqiqt+5+Z1TWzuWb2vpktNLPbQvmtZva5mc0Pt9Nj9rnZzJaY2UdmdmpM+dFmlh+23W9h8JOZ1TGz50P5HDPLqqzXJyIiIiLV08KFCznhhBO45JJL6Ny5M++//z4TJ05k9OjRtG3bFjOjbdu2jBo1ao+vTSo1Q2W2VG0Cfubu68ysNjDTzF4L20a4+12xlc2sIzAAOBw4EPi3mR3i7kXASCAbeBt4FegLvAYMA75194PNbABwJ/DLSnhtIiIiIlLNbNiwgdtvv5277rqLxo0bM2bMGC666KLtk5UNHDhQSZQkpNJaqjyyLjytHW6lzQTRD3jO3Te5+1JgCdDdzFoA+7r7Wx51dn0K6B+zz5Ph8YtAn+JWLBERERGRYv/85z/p1KkTd9xxB4MGDeLDDz9k6NChNWr2Z6k8lTqmyswygHeAg4F/uPscMzsN+I2ZDQHmAde5+7dAS6KWqGIrQ9mW8LhkOeH+MwB332pm3wP7AWtKxJFN1NJFZmYmeXl5e/Jl1kjr1q3T+1RD6FpWHL23NYuuZ82ha1n15efvl3DdjRsLyc/PT7h+o0YFOz0vKCjgwQcfJC8vj9atWzNixAi6du3KBx98kPAxRUqq1KQqdN3ramY/AiaaWSeirny3E7Va3Q7cDVwMxPuZwEspp4xtsXGMAkYBNGjQwHv37p3cC9kL5eXlofepZtC1rDh6b2sWXc+aQ9ey6lu7NvG6+fn5dO7cOeH6xZe+qKiIRx55hJtvvplNmzbx5z//mRtuuIE6deokF6xIHGlZp8rdvwPygL7u/rW7F7n7NmA00D1UWwm0jtmtFfBFKG8Vp3ynfcwsE2gMfFNBL0NEREREqoH58+fTs2dPrrzySrp3705+fj5//OMflVDJHlOZs//tH1qoMLN6wEnAh2GMVLGzgOK21ynAgDCjXzugAzDX3b8E1ppZjzBeaggwOWafC8Pjc4E3XSv4ioiIiOyVCgsLue666+jWrRvLli1j7NixvP7663To0CHdoUkNU5nd/1oAT4ZxVbWAce7+spk9bWZdibrpLQMuBXD3hWY2DlgEbAWuDN0HAS4HngDqEc36VzyL4GPA02a2hKiFakBlvDARERERqVrmzJnDI488wpo1j5Odnc0dd9xBkyZN0h2W1FCVllS5+wJgl9Vj3X1wKfvkALussObu84BOcco3AuelFqmIiIiIVFerV69m1KhRzJnzNm3atGXmzJn06tUr3WEJYGZjgF8Aq9y9Uyj7O3AGsBn4BBgahgphZjcTLZlUBFzl7v8K5Uezo4HlVeBqd3czq0M0M/jRQAHwS3dfVhmvLS1jqkRERERE9qSioiImT57MlVdeyXvvvceQIRdy7733KqGqWp4gWl821htAJ3fvAvwfcDPssmZtX+Ch0OMNdqxZ2yHcio+5fc1aYATRmrWVolJn/xMRERER2dM+/vj/+Mc/HuLTTz/h6KO7cdlll9K8+Y/THZaU4O4zzCyrRNnrMU/fJpoXAWAni9IAACAASURBVGLWrAWWhuE93c1sGWHNWgAzK16z9rWwz61h/xeBB83MKmOOBSVVIiIiIlItrV+/nrFjx/LKK6/QpEkTbrzxJnr27KkFfNMj08zmxTwfFZYxSsbFwPPhcYWtWVsRlFSJiIiISJWXl5fH008/zerVq2nWrBk9evRg1qxZfPvtt/z85z9n0KBBNGjQIN1h7s22unu38u5sZsOJJqfLLS6KU22PrFlbEZRUiYiIiEiVlpeXx4MPPsjmzZsAWLNmNS+//BL7738Ad999Fx06HJLmCCUVZnYh0QQWfWK66qWyZu3Kyl6zVhNViIiIiEiV9vTTT29PqGK5uxKqas7M+gI3Ame6+4aYTdVqzVq1VImIiIhIlbZ69eq45WvWVPhQGdmDzOxZoDfQzMxWArcQzfZXB3gjjIV7290vq25r1iqpEhEREZEqbf/992f16lVxy6X6cPcL4hQ/Vkr9arNmrbr/iYiIiEiVNnjwYGrVytipbJ996jB48OA0RSSyMyVVIiIiIlKl9erVi9q1a7PPPnUAY//9D+A3v/kNvXv3TndoIoC6/4mIiIhIFffuu++yadNG/vSnW6hTpw6dO3dOd0giO1FLlYiIiIhUaXl5eey7b2O6du2a7lBE4lJSJSIiIiJV1vr165kzZw7HH388mZnqZCVVk5IqEREREamyZs+ezdatWzR+Sqo0JVUiIiIiUmVNnz6dFi0OpEOHDukORWS3lFSJiIiISJW0Zs0aFixYQO/evQkLw4pUSUqqRERERKRKmjFjBuCccMIJ6Q5FpFRKqkRERESkSsrLy+PQQ3/CgQcemO5QREqlpEpEREREqpylS5eybNlSTVAh1YKSKhERERGpcqZPn06tWhkcd9xx6Q5FpExKqkRERESkStm2bRvTp0/nqKOOonHjxukOR6RMlZZUmVldM5trZu+b2UIzuy2UNzWzN8zs43DfJGafm81siZl9ZGanxpQfbWb5Ydv9FqaDMbM6ZvZ8KJ9jZlmV9fpEREREZM9YuHAhBQVr1PVPqo3KbKnaBPzM3Y8AugJ9zawHcBMw1d07AFPDc8ysIzAAOBzoCzxkZhnhWCOBbKBDuPUN5cOAb939YGAEcGdlvDARERER2XPy8vKoW7ceP/3pT9MdikhCKi2p8si68LR2uDnQD3gylD8J9A+P+wHPufsmd18KLAG6m1kLYF93f8vdHXiqxD7Fx3oR6GNa1EBERESk2ti8eTMzZ86kZ8+e1KlTJ93hiCQkszJPFlqa3gEOBv7h7nPMrLm7fwng7l+a2QGhekvg7ZjdV4ayLeFxyfLifT4Lx9pqZt8D+wFrSsSRTdTSRWZmJnl5eXvsNdZU69at0/tUQ+haVhy9tzWLrmfNoWtZ9eXn77f98QcffEBh4Qbatm1Lfn7+LnU3biyMW747jRoV7JEYRUpTqUmVuxcBXc3sR8BEM+tUSvV4LUxeSnlp+5SMYxQwCqBBgwau/rply8vLU7/mGkLXsuLova1ZdD1rDl3Lqm/t2h2Pp0yZQpMmTTnzzDPJyMjYpW5+fj6dO3dO+Ni69FIZ0jL7n7t/B+QRjYX6OnTpI9yvCtVWAq1jdmsFfBHKW8Up32kfM8sEGgPfVMiLEBEREZE9au3atcybN4/jjz8+bkIlUlVV5ux/+4cWKsysHnAS8CEwBbgwVLsQmBweTwEGhBn92hFNSDE3dBVca2Y9wnipISX2KT7WucCbYdyViIiIiFRxs2bNoqhoq1oWpdqpzO5/LYAnw7iqWsA4d3/ZzN4CxpnZMGAFcB6Auy80s3HAImArcGXoPghwOfAEUA94LdwAHgOeNrMlRC1UAyrllYmIiIhIyqZNm0br1m046KCD0h2KSFIqLaly9wXAkXHKC4A+u9knB8iJUz4P2GU8lrtvJCRlIiIiIlJ9fP311yxevIjBg4egyZuluknLmCoRERERkVjTp08H4IQTTkhzJCLJU1IlIiIiImnl7kybNo2OHQ/ngAMOKHsHkSpGSZWIiIiIpNWnn37K55+v1AQVUm0pqRIRERGRtJo2bRqZmbU57rjj0h2KSLkoqRIRERGRtCkqKmLGjBl069aNhg0bpjscqUBmNsbMVpnZBzFlTc3sDTP7ONw3idl2s5ktMbOPzOzUmPKjzSw/bLs/LLNEWIrp+VA+x8yyKuu1KakSERERkbR58803+e67b9X1b+/wBNC3RNlNwFR37wBMDc8xs45EyyMdHvZ5KCzNBDASyCZax7ZDzDGHAd+6+8HACODOCnslJSipEhEREZG0GTt2LPXrN6Bbt27pDkUqmLvPIFpLNlY/4Mnw+Emgf0z5c+6+yd2XAkuA7mbWAtjX3d9ydweeKrFP8bFeBPpYJc3Pr6RKRERERNJi/fr1TJgwgV69erHPPvukOxxJTaaZzYu5ZSe4X3N3/xIg3BdP/9gS+Cym3spQ1jI8Llm+0z7uvhX4HtivPC8mWZW2+K+IiIiISKwpU6awbt06TjzxxHSHIqnb6u57srkxXguTl1Je2j4VTi1VIiIiIpIWY8eOpXXr1nTs2DHdoUj6fB269BHuV4XylUDrmHqtgC9Ceas45TvtY2aZQGN27W5YIdRSJSIiIiKVbvXq1fzrX//i+uuvp1Yt/c6/F5sCXAjcEe4nx5Q/Y2b3AAcSTUgx192LzGytmfUA5gBDgAdKHOst4FzgzTDuahdmjEk0QHcuLquOkioRERERqXTPP/88RUVFDBo0iKVL0x2NVAYzexboDTQzs5XALUTJ1DgzGwasAM4DcPeFZjYOWARsBa5096JwqMuJZhKsB7wWbgCPAU+b2RKiFqoBpYSzf4nnxwPbgPzwvBNRr74Zibw2JVUiIiIiUunGjh3LEUccQadOnZRU7SXc/YLdbOqzm/o5QE6c8nlESU/J8o2EpKzsWDij+LEZNwOFwFB31oeyBkRJWn78I+xMba0iIiIiUqk+/vhj5syZw6BBg9IdigjAVcCtxQkVQHh8O/DbRA6gpEpEREREKlVubi5mxgUX7K7hQqRSNSQat1VSC6B+IgdQUiUiIiIilcbdyc3N5cQTT6Rly5Zl7yBS8cYDj5sxwIyscBtA1P1vQiIHUFIlIiIiIpVm7ty5LFmyRF3/pCq5HHiJaPKLT8LtSeAV4IpEDqCJKkRERESk0owdO5a6dety9tlnpzsUEQDcKQSuMOP3QHuiRYSXxI6xKotaqkRERESkUmzZsoXnnnuOM888k8aNG6c7HJGS6oXbh8kkVKCkSkREREQqyeuvv86aNWvU9U+qFDMamfECsAqYDbQM5Q+bcWsix1BSJSIiIiKVIjc3l6ZNm3LqqaemOxSRWHcSzf53FNF6VcVeBs5K5ACVllSZWWszm2Zmi81soZldHcpvNbPPzWx+uJ0es8/NZrbEzD4ys1Njyo82s/yw7X4zs1Bex8yeD+VzzCyrsl6fiIiIiOze2rVrmTRpEr/85S/ZZ5990h2OSKwzgWvcmQ94TPli4KBEDlCZLVVbgevc/TCgB3ClmXUM20a4e9dwexUgbBsAHA70BR4ys4xQfySQDXQIt76hfBjwrbsfDIwgyjpFREREJM0mTpxIYWGhuv5JVdQEKIhT3ggoSuQAlZZUufuX7v5ueLyWKPMrbXGCfsBz7r7J3ZcCS4DuZtYC2Nfd33J3B54C+sfs82R4/CLQp7gVS0RERETSZ+zYsbRr145jjz023aGIlPRfotaqYsWtVZcSjbEqU1qmVA/d8o4E5gC9gN+Y2RBgHlFr1rdECdfbMbutDGVbwuOS5YT7zwDcfauZfQ/sB6wpcf5sopYuMjMzycvL23MvroZat26d3qcaQtey4ui9rVl0PWsOXcv0KygoYOrUqQwcOJDp06fvsj0/f7+Ej7VxYyH5+fkJ12/UKF4DhMhO/gD8y4zDifKja8Pj7sDxiRyg0pMqM2tItGrxNe7+g5mNBG4nyghvB+4GLiaaH74kL6WcMrbtKHAfBYwCaNCggffu3TvJV7H3ycvLQ+9TzaBrWXH03tYsup41h65l+o0YMYJt27YxfPhwDj300F22r12b+LHy8/Pp3LlzwvV16aUs7sw2oydwPdHCv32Ad4Fj3Ukog6/UpMrMahMlVLnuPgHA3b+O2T6aaJYNiFqgWsfs3gr4IpS3ilMeu89KM8sEGgPf7PlXIiIiIiKJGjt2LN26dYubUIlUBSF5urC8+5eaVJnZmMQD8YvLOJYBjwGL3f2emPIW7v5leHoW8EF4PAV4xszuIZrisAMw192LzGytmfUg6j44BHggZp8LgbeAc4E3w7grEREREUmDRYsW8e6773LvvfemOxSRUpnRFDiAEvNOuLOorH3Laqnav8Tz44FtsL0ZrFM46YwE4uwFDAbyzWx+KPsDcIGZdSXqpreMaEAY7r7QzMYBi4hmDrzS3Ytn37gceIJoxePXwg2ipO1pM1tC1EI1IIG4RERERKSC5ObmkpGRwYAB+lomVZMZRwKPA8X9So0dw44cyNjNrtuVmlS5+xk7TmY3Ey2GNdTd14eyBkSJTJl9Dd19JvHHPL1ayj45QE6c8nlECV3J8o3AeWXFIiIiIiIVb9u2beTm5nLyySfTvHnzdIcjsjtjgM+Bq4GviTMnQ1mSGVN1FdCnOKECcPf1ZnY7MJU4yY+IiIiI7L1mz57N8uXL+ctf/pLuUERK0wE4z50l5T1AMutUNSQa21RSC6B+eQMQERERkZpp7Nix1K9fn/79+5ddWSR9ZgKHpXKAZFqqxgOPm9nv2bF+VA/gTmBCKkGIiIiISM2yadMmxo0bx1lnnUXDhg3THY5IaYYBj5pxENGkeVtiN7qXPX9EMknV5URrSD0B1A5lW4nGVF2fxHFEREREpIZ77bXX+Pbbbxk0aFC6QxEpSwegK3BqnG2pT1Sx09HcC4ErQktVe6JJJ5bEjrESEREREYGo698BBxzASSedlO5QRMryCNEcEf9LJUxUUaxeuM13903l2F9EREREarDvvvuOl19+mUsvvZTMzPJ83RSpVK2A0935pLwHSHiiCjNrZGYvAKuA2UDLUP6wmd1a3gBEREREpGYZP348mzZtUtc/qS7eAI5O5QDJ/HRwJ9Hsf0cRzZBR7GWi6dRvTSUQEREREakZxo4dyyGHHEK3bt3SHYpIIv4J3G1GF6L1d0tOVFHmpHzJJFVnAme5+3wzi+1nuBg4KInjiIiIiEgNtWLFCvLy8vjzn/+MmaU7HJFEPBTu/xBnW0ITVSSzTlUToCBOeSOgKInjiIiIiEgN9eyzzwIwcODANEciVY2Z/c7MFprZB2b2rJnVNbOmZvaGmX0c7pvE1L/ZzJaY2UdmdmpM+dFmlh+23W8pZu/u1CrlVmZCBcklVf8laq3afv5wfynRGCsRERER2cvl5uZy7LHHctBB6sgkO5hZS+AqoJu7dyJq/RkA3ARMdfcORDPw3RTqdwzbDwf6Ag+ZWXGCMxLIJpoKvUPYXs64qG3GHDMOLe8xILmk6g/A7WY2mqjb4LVm9iYwGPh/qQQhIiIiItXfggULyM/P1wQVsjuZQD0zywTqA18A/YAnw/Yngf7hcT/gOXff5O5LgSVAdzNrAezr7m+5uwNPxeyTNHe2AO0oxzTqsRJOqtx9NtAT2Af4BOhD9EYc6+7vphKEiIiIiFR/Y8eOJTMzk/PPPz/doUjlyzSzeTG37NiN7v45cBewAvgS+N7dXweau/uXoc6XwAFhl5bAZzGHWBnKWobHJctT8SRwSSoHSGrhAHfPBy5M5YQiIiIiUvMUFRXxzDPPcNppp9GsWbN0hyOVb6u773a6xzBWqh9Rq9B3wAtmVlqTZrxxUl5KeSoaAAPNOBl4B1i/08Gdq8o6QNKrsZlZU6IMcqdWLndflOyxRERERKRmmD59Op9//jn33HNPukORqukkYKm7rwYwswlEveC+NrMW7v5l6Nq3KtRfCbSO2b8VUS+5leFxyfJUHAYU97wrORgwoYQt4aTKzI4EHgc6FxexI1tMaKpBEREREamZcnNzadSoEWeccUa6Q5GqaQXQw8zqA4VEQ4nmEbUKXQjcEe4nh/pTgGfM7B6itXI7AHPdvcjM1ppZD2AOMAR4IJXA3Dkxlf0huZaqMcDnwNXA16TezCYiIiIiNUBhYSEvvvgi55xzDvXq1Ut3OFIFufscM3uRqEVoK/AeMApoCIwzs2FEidd5of5CMxsHLAr1r3T34mWcLgeeAOoBr4VbWiWTVHUAznP3JRUVjIiIiIhUPy+//DI//PCDZv2TUrn7LcAtJYo3EbVaxaufA+TEKZ8HdEolFjOmAIPc+SE83i33nZaViiuZpGomUX9DJVUiIiIist3YsWM58MAD6d27d7pDEUlUATt63n1Dir3wkkmqhgGPmtlBwAfAltiN7j4jlUBEREREpPpZs2YNr776Ktdccw0ZGRpiL9XG40Rju3DnolQPlmz3v67AqXG2aaIKERERkb3QCy+8wNatW9X1T6qbaUALYJUZnwLHuFNQ3oMlvPgv8AgwlWj2vwOA/WNuB5SyHwBm1trMppnZYjNbaGZXh/KmZvaGmX0c7pvE7HOzmS0xs4/M7NSY8qPNLD9su9/MLJTXMbPnQ/kcM8tK4vWJiIiISJJyc3M5/PDD6dKlS7pDEUnGt0RrZgFkkVxetItkdm4F3OLuC919jbsXxN4S2H8rcJ27Hwb0AK40s47ATcBUd+9AlLTdBBC2DQAOB/oCD5lZcWvYSCCbqPWsQ9gOURfFb939YGAEcGcSr09EREREkvDpp58ya9YsBg0aRPiNW6S6GA9MN2MpUa+7eWZ8Gu+WyMGS6f73BnA08EnyMYO7fwl8GR6vNbPFQEuilZV7h2pPAnnAjaH8OXffBCw1syVAdzNbBuzr7m8BmNlTQH+iqRT7AbeGY70IPGhm5u6a/l1ERERkD3vmmWcA+NWvfpXmSESSdhnRWlgdgHuIxlitLe/Bkkmq/gncbWZdgHx2nahiQqIHCt3yjiRasKt5SLgIKykXdyVsCbwds9vKULYlPC5ZXrzPZ+FYW83se2A/YE2J82cTtXSRmZlJXl5eoqHvtdatW6f3qYbQtaw4em9rFl3PmkPXcs/797//zejRo1m1ahW1a9dm1KhRnHTSSeU+Xn7+fgnX3bixkPz8/ITrN2pU7mEyUoO548ArAGYcAdztXjlJ1UPh/g/x4iLBiSrMrCFRc9s17v5DKU3F8TZ4KeWl7bNzgfsoosXGaNCggWv6z7Ll5eVpmtQaQtey4ui9rVl0PWsOXcs9Kzc3lxEjRrBhwwYAtmzZwogRIzjssMMYOHBguY65Nomvsvn5+XTu3Dnh+rr0UhZ3hqZ6jITHVLl7rVJuiSZUtYkSqtyYlq2vzaxF2N4CWBXKVwKtY3ZvBXwRylvFKd9pHzPLBBoTzTsvIiIiIinYvHkzc+bM4be//e32hKrYhg0bGD58eJoiE0mNGXXNuNGM182Yb8aC2Fsix0iopSokQzOBIe7+UfmCNQMeAxa7+z0xm6YAFwJ3hPvJMeXPmNk9wIFE/R3nunuRma01sx5E3QeHAA+UONZbwLnAmxpPJSIiIpK8goICZs+ezezZs5k1axb//e9/2bhx427rr1ixohKjE9mjHgLOAl4AZlOOhYATSqrcfYuZtSvPCWL0AgYD+WY2P5T9gSiZGmdmw4AVwHnhnAvNbBywiGjmwCvdvSjsdznwBFCPaIKK10L5Y8DTYVKLb4hmDxQRERGRUrg7H3300fYEatasWXz0UfQ7eu3atTnqqKO4/PLL6dWrF1dffTWff/75Lsdo06ZNZYctsqf0B85z59/lPUAyY6qeBC4Bfl+eE7n7TOKPeQLos5t9coCcOOXzgE5xyjcSkjIRERERia+wsJB58+Yxa9as7a1RBQXRhA5NmzalZ8+eXHTRRfTs2ZNjjjmGevXqbd9348aNZGdn79QFsH79+uTk7PKVTaS62ECY7K68kkmqGgADzexk4B1gfexGd78qlUBEREREJHm5ubkMHz6cFStW0KZNG3JycnaZMOKrr77aqRXq3XffZcuWaCLnQw89lDPPPJNevXrRq1cvDjnkEGrV2v2w++Jjl3VOkWrkb8C1ZlzuzrbyHCCZpOow4N3w+KAS2zRuSURERKSS5ebm7tRqtHz5crKzs/nss8/40Y9+tD2R+vTTaP3SOnXqcMwxx3DttdfSq1cvjj32WJo1a5b0eQcOHKgkSmqSk4H/AfqasYhdlo7izLIOkHBS5e4nJh2eiIiIiFSY4cOHx52J7+abbwagefPm9OrViyuuuIJevXpx1FFHsc8++6QjVJGqbA0wMZUDJNNSJSIiIiJVQFFREbNmzWL58uW7rfPJJ5/Qrl07SlkTVETYM+tUlZpUmdkUYFBYpHdK6cF4mc1iIiIiIlI+mzdvZtq0aUyYMIFJkyaxatWq3dZt27YtBx1UcrSGiJTGjIOAjkRDmxa782mi+5bVUlXAjvFS36CxUyIiIiKVprCwkNdff53x48fz0ksv8d1339GwYUN+/vOfc84557B27dpdFuPVTHwiyTFjX6Klmc6B7RNVmBnjgWHurC3rGGUlVY8DhQDuflH5QxURERGRRKxdu5ZXXnmFCRMm8Oqrr7J+/XqaNGlC//79Ofvsszn55JOpW7fu9vp16tTRTHwiqbkP6AKcSLT4L0Rr7D4M3AsMK+sAZSVV04AWwCoz+xQ4xt0Lyh2uiIiIiOyioKCAl156ifHjx/PGG2+wadMmmjdvzuDBgznnnHM44YQTqF27dtx9NROfSMrOBPq785+YsjwzsokmsEg5qfoWaAesArKA3S9aICIiIiIJ++qrr5g4cSITJkxg2rRpFBUV0bZtW6644grOPvtsjj32WDIyMtIdpsjeoB7RsKeSvgHqxinfRVlJ1Xhgupl9STSeap6ZFcWr6O4aDSkiIiJSimXLljFx4kTGjx/P7NmzcXcOOeQQbrjhBs455xyOOuoozdYnUvlmAbebMdidDQBmNABuY0d3wFKVlVRdBkwBOgD3EI2xKnOgloiIiMjeKDc3d5fxTd26dWP8+PGMHz+ed999F4CuXbty2223cfbZZ9OxY0clUiLp9Tvgn8DnZiwgakw6AlgPnJrIAUpNqtzdgVcAzOwI4G53V1IlIiIiUkJubi7Z2dnbZ+Jbvnw5gwcPJvo6BT169ODvf/87Z511Fu3bt09nqCISw50PzOgADAJ+AhgwFsh1jybtK0vCi/+6e8qLYomIiIjUVDfddNNOU5sDuDtNmjQhPz+fli1bpikyESlLSJ5Gl3f/hJMqM6sLXA30AQ6gxKQV7t6lvEGIiIiIVEfuzltvvcWoUaNYuXJl3DrfffedEiqRKsyMHOAzdx4uUX4Z0NKdP5Z1jGRm83sIuAlYBkwimsQi9iYiIiKyV/jmm2+4//776dy5M7169WLChAk0bNgwbt02bdpUcnQiVZOZ/cjMXjSzD81ssZkda2ZNzewNM/s43DeJqX+zmS0xs4/M7NSY8qPNLD9su99SH5Q4GHgvTvk7wJBEDpBMUtUfOM/ds939Vne/LfaWxHFEREREqh13Z+bMmQwZMoSWLVty9dVX06BBAx577DG++OILHn74YerXr7/TPvXr1ycnJydNEYtUOfcB/3T3nxBNBLGYqNFmqrt3AKaG55hZR2AAcDjQF3jIzIrXGBgJZBNNptchbE/FAcDqOOUFQPNEDpBw9z9gA/BZEvVFREREqr2CggKefvppRo0axeLFi9l3330ZNmwYl1xyCUccccT2esUL8Jac/U8L84qAme0LHA/8f/buPD6q6v7/+OuTBcImEBBkTRQRBcIim1slQouKFrAqLhRsXaJUf1rpIsjXpbaxLnVBrdi4B1OVugEVrAtELCIICqYQFRSDQQQTtgAJCcn5/TGTmJBJSJgkdzJ5Px+PeUzm3O1z751gPp5zP+dXAM65QqDQzMYDif7VngfSgVuA8cBLzrkDwCYz2wgMN7NvgKOcc8v9+03F1/mzKIjwNgM/Ab4+pP1MIPC43kPUJqm6D5hmZlOdcyW12E5ERESkUXHO8cEHH5CSksIrr7zCgQMHOOWUU3j22We5+OKLadWqVcDtJk2apCRKmqooM1tV7nOKcy6l3Ofj8PUGPeuvKr4aX72Gzs65rQDOua1m1sm/fjfgo3LbZ/vbiqiY6JS2B+MfwENmNAMW+9tGA38F7q3JDmqTVP0MXwZ3jpmtx3dCZZxz42qxLxEREZGQk5OTQ2pqKikpKXzxxRe0bduWpKQkrrnmGhISErwOTySUHXTODa1meRRwMvD/nHMrzGwW/qF+VQj0nJSrpv2IOccDZnQEHgGa+ZsLgVnOcV9N9lGbpCoHeL12IYqIiIiENucc6enppKSk8Nprr1FYWMhpp53G888/z0UXXVTpOSkROSLZQLZzboX/8yv4kqptZtbF30vVBdhebv0e5bbvDnznb+8eoD0ozjHDjL8AffElbuudY2/5dcx8x3KOSqP2NE+ViIiINEk//PADzz33HE8++SQbNmygXbt2TJ06lWuuuYZ+/fp5HZ5IWHHOfW9m35pZH+fcF/iG1633v64A7vG/z/NvMh/4p5k9CHTFV5BipXOu2MzyzOwUYAW+6nyP1k2M7AM+rmaV9cAgKj97VavqfwCY2XFmdr6ZnWdmx9Viu2fMbLuZ/a9c251mtsXM1vhfY8stq1UJRTNrbmYv+9tXmFl8bc9NREREwkdaWhrx8fGMGjWK+Ph40tLSKCkp4b333uOSSy6hW7du/PGPf6Rz587MmTOH7777jocfflgJlUj9+X9Ampl9hi85uRtfMvUzM9uA73GjewCcc+uAufgSmbeA651zxf79TAWeAjYCXxFckYraqLJ0e20m/z0KeBq4EMq6vMzMXgWucs7lHWYXzwGPAamHtD/knPvbIccqX0KxK/CumZ3gv5ClJRQ/F7pCkQAAIABJREFUAhbiK6G4CLgK2OmcO97MLsX3UNklNT0/ERERCR9paWkkJSWxf/9+ALKysvj1r3/NtGnT2L59O7Gxsdxwww1cffXV9O3b1+NoRZoG59waINBzV6OrWD8ZqDQngXNuFdC/bqMLTm16qmYBA4CzgBb+12h/28OH29g5txTYUcNjlZVQdM5twpeFDvePszzKObfcOefwJWgTym3zvP/nV4DRdTARmIiIiDRCM2fOLEuoShUVFbF7927S0tLYsmULDz74oBIqEakTtSlUMQ6Y4Jz7oFxbupkl4StgcdURxnCDmU0BVgG/c87t5MhKKHbDP4+Wc+6gme0GOuArsFGBP+YkgKioKNLT048w9KZj7969uk5hQvey/ujahhfdz8anpKSEjRs3smLFCrKysgKuU1hYSNeuXfnoo48CLhdvZGR0qPG6BQX5ZGRk1Hj9Nm1yjyQkkVqpTVLVAt+swofaAcQc4fFnA3/GVwbxz8ADwJUcWQnFGpdX9NfMTwFo1aqVS0xMrFXQTVF6ejq6TuFB97L+6NqGF93PxmHnzp288847LFy4kLfeeott27YB0KxZMwoLCyut37NnT93XEJR3uIdIysnIyKhVeXvdbqlDVZZur83wv2XAn82srK6ombUC/gR8eERRObfNOVfsn0z4SWC4f9GRlFAs28bMooC21Hy4oYiIiDQCzjk+/fRTkpOTOeOMM+jYsSOXXHIJCxYs4KyzziI1NZVt27bxzDPPVCqF3rJlS5KTKz2eISJSU8EXqgCm4au8scVfscMBA4H9wJgjispfk97/8QKgtDLgkZRQnI+vDONy4CJgsf+5KxEREWnESnujFi1axFtvvcX3338PwJAhQ5g5cybnnnsuw4cPJzIysmybSZMmAb5nqzZv3kzPnj1JTk4uaxcRKWXGqcBK5yg+zKp9qWJOrNrMU5VhZscDvwROxJepvQCkOefyDx+svQgkAh3NLBu4A0g0s0H4ErRvgGv9x1pnZqUlFA9SuYTic/iGIy7ixxKKTwNzzGwjvh6qS2t6biIiIhI6nHOsXbuWhQsXsmjRIpYvX05xcTHt27dnzJgxjB07lrPPPpvOnTtXu59JkyYxadIkDeUUkcNJBwrN+ND/czoBkiznfPUbAqlNSfVk4Fvn3BOHtF9nZt2cc7dVt71z7rIAzU9Xs36tSig65wqAi6uLQURERLyRlpZWba/Rrl27ePfdd8uejdq61TeQ5eSTT2b69OmMHTuW4cOHExVVm0E2IiI10g44AxgJnAfcyY9J1hLnfHNnVac2/zJNJnDS8gkwA6g2qRIREZGmKdCcUUlJSWzevBmARYsW8eGHH1JcXEy7du0q9EYdc8wxXoYuIk2Ac+QD7/hfmHE8MBPfCL2fQt0mVZ2AHwK05wDV97+LiIhIkxVozqj9+/dz6623AjB48GBuueUWxo4dy4gRI9QbJSINyoxO+B5TOsv/HgesxDdqbklN9lGbf7U2Az8Bvj6k/Uwqzh0lIiIiUqa0RyqQ7777ji5dujRgNCIilXyPr/MoBbgO+Mg5DtRmB7VJqv4BPGRmzYDF/rbRwF+Be2tzUBEREQlvxcXFLFy4kMcff5yqivHGxcUpoRKRUPAivo6im4DBwBIz0oFPnKt6bqryalP97wEz6wg8AjTzNxcCs5xz99UmahEREQlP27Zt4+mnn+Yf//gHmzdvpmvXrvziF79g0aJF5Of/WCxYc0aJSKhwjkkAZvTGV6wiEV+C1caMpc4x/nD7qM3kvzjnZgAdgVOAU4GjnXPTaxm3iIiIhBHnHEuXLuWyyy6jR48ezJw5k969e/PKK6/wzTff8Oqrr/Lkk08SFxeHmREXF0dKSormjBKRUPMVkAGsAz4HWgPn1GTDWj8J6pzbB3xc2+1EREQkvOzZs4c5c+Ywe/Zs1q1bR7t27bj++uu57rrr6NOnT4V1S+eMEhEJNWb8AV+RijOA5viqm78PPAh8UJN9qLyOiIiI1MratWuZPXs2L7zwAvv27WPIkCE8/fTTXHrppbRs2dLr8EREautCfBP+PgJ84Bz7arsDJVUiIiJyWAUFBbzyyivMnj2bDz/8kJiYGC677DKmTp3KsGHDvA5PROSIOccpwe5DSZWIiIhU6euvv+Yf//gHzzzzDDk5OfTu3ZsHH3yQK664gtjYWK/DExGpE2YkANcCvYArnWOrGROALOf49HDbK6kSERGRCkrLoc+ePZu33nqLiIgIxo0bx29+8xtGjRpFRESt6lyJiIQ0M8YA84FFwCighX9RL+BXwITD7UP/KoqIiDRBaWlpxMfHExERQXx8PGlpaWzbto27776bXr16MW7cONasWcPtt99OVlYWr732Gj/96U+VUIlIOPozMM05LsA3ZVSpdGB4TXagnioREZEmJi0tjaSkJPbv3w9AVlYWV1xxBc45SkpKGDVqFA888ADjxo0jOjra42hFROpdP2BhgPYdQI3GOSupEhERaWJmzpxZllCVKi4upk2bNqxcuZITTzzRo8hERDyxE+gGfHNI+8lAdk12oKRKRESkifjyyy+ZN28eWVlZAZfv3btXCZWINEX/BO43YyLggCgzRgJ/A56tyQ6UVImIiISpkpISPv74Y+bNm8cbb7xBZmYmANHR0RQVFVVav2fPng0doohIKPg/4DkgCzBgPb7aE2nA3TXZgZIqERGRMFJYWMiSJUt44403mDdvHlu3biUyMpKRI0cydepUxo0bx3//+98Kz1QBtGzZkuTkZA8jFxHxhnMUAZPMuA3fkL8I4FPn2FDTfSipEhERaeR2797NokWLeOONN1i4cCF5eXm0atWKc845hwkTJjB27NgKc0rFxcUBvmerNm/eTM+ePUlOTmbSpElenYKIiKfMuAQYDXTCl1T90sy3zDnGHW57JVUiIiKN0JYtW5g/fz7z5s1j8eLFFBUV0alTJy655BImTJjA6NGjiYmJqXL7SZMmKYkSEQHMuB/4LbAE+A7fc1W1oqRKRESkEXDOkZmZWfZ81MqVKwE4/vjj+e1vf8uECRMYMWIEkZGRHkcqIlI1M4sEVgFbnHPnm1ks8DIQj6/63kTn3E7/ujOAq4Bi4Ebn3H/87UPwPQPVAl8p9Jucc7VOhMqZAlzmHK8c6Q40g5+IiIjHAk3EC74y58uWLeOPf/wjffr0oV+/ftx6660AJCcns27dOr788kvuu+8+TjvtNCVUItIY3ARklvs8HXjPOdcbeM//GTPrC1yKbw6pc4DH/QkZwGwgCejtf50TZEwRwJpgd9AgzOwZM9tuZv8r1xZrZu+Y2Qb/e/tyy2aY2UYz+8LMzi7XPsTMMvzLHjHzjXY0s+Zm9rK/fYWZxTfUuYmIiByp0ol4s7KycM6RlZXFVVddxVlnnUXXrl0544wzePjhhzn22GN5/PHHyc7OZsWKFdx666307dsXKx30LyIS4sysO3Ae8FS55vHA8/6fnwcmlGt/yTl3wDm3CdgIDDezLsBRzrnl/t6p1HLbHKkU4JfB7KAhh/89BzyG78RLlWam95jZdP/nWw7JTLsC75rZCc65Yn7MTD/C1913DrAIX9fgTufc8WZ2KXAvcEmDnJmIiMgRCjQR74EDB3j//feZOHEiEyZM4Nxzz6Vt27YeRSgiUiNRZraq3OcU51zKIes8DPwRaFOurbNzbiuAc26rmXXyt3fD9/d+qWx/WxEVJ+QtbQ9GO+ByM34GfOY/RhnnuPFwO2iwpMo5tzRA79F4INH/8/NAOnAL5TJTYJOZlWam3+DPTAHMrDQzXeTf5k7/vl4BHjMzC3J8pYiISL0oLi5myZIlVU7EC/DSSy81YEQiIkE56JwbWtVCMzsf2O6cW21miTXYX6BueFdNezD68uPwv0NnQK/Rvr0uVFGXmWk34Fv/vg6a2W6gA5Bz6EHNLAlfbxdRUVGkp6fX1fmErb179+o6hQndy/qjaxte6ut+btq0ibfffpt3332XnJwczIxA//+vU6dO+j7VEf1uhr6MjA41XregIJ+MjIwar9+mTe6RhCR173RgnJmNBWKAo8zsBWCbmXXx5wJdgO3+9bOBHuW2746vMl+2/+dD24+Yc5wVzPbgfVJVlSPJTGuctfq7IlMAWrVq5RITE48gxKYlPT0dXafwoHtZf3Rtw0td3s/t27fz4osvkpqayieffEJkZCTnnnsuU6ZMYd++fVx//fWVJuJ94IEH9H2qI/rdDH15eTVfNyMjg4SEhBqvr1sfGpxzM4AZAP6eqt87535pZvcDVwD3+N/n+TeZD/zTzB7E9zhQb2Clc67YzPLM7BRgBb7KfY826MkE4HVSVZeZaek22WYWBbQFdtRn8CIiIlUpKChg/vz5pKam8tZbb1FcXMyQIUOYNWsWl156KZ06dSpbNzo6WhPxikhTdQ8w18yuAjYDFwM459aZ2VxgPXAQuN5fXwFgKj+WVF/kf3nK66RqPnWXmZbuazlwEbBYz1OJiEhDcs6xbNkyUlNTmTt3Lrt376Zbt278/ve/Z/LkyfTr1y/gdpqIV0SaEudcOr5aCjjncoHRVayXDCQHaF8F9K+/CGuvwZIqM3sRX1GKjmaWDdxB3WamTwNz/EUtduCrHigiIlLvNm7cyJw5c5gzZw6bNm2iVatWXHjhhUyZMoXExETNHyUiEuYasvrfZVUsqpPM1DlXgD8pExERqW87d+5k7ty5pKam8uGHH2JmjB49mj/96U9ccMEFtG7d2usQRUSkgXg9/E9ERKTRKCoqYtGiRcyZM4f58+dTWFhI3759uffee7n88svp3r374XciIiJhR0mViIhIOWlpaZWKRvTp04fU1FRefPFFcnJyOProo5k6dSpTpkxh8ODBmAUqQCsiIk2FkioRERG/tLQ0kpKSysqbZ2VlMXnyZJxzNG/enPHjxzNlyhTGjBlDdHS0x9GKiEioUFIlIiLid+utt1aYLwp8Ff1iY2P56quvaNeunUeRiYhIKFNSJSIiTV5WVhZPPvkkmzdvDrh8586dSqhERKRKSqpERKRJKi4u5q233uKJJ55g4cKFOOdo0aIF+fn5ldbt2bOnBxGKiEhjEeF1ACIiIg1p27Zt3H333fTq1Yvzzz+fjz/+mBkzZrBp0yaefPJJWrZsWWH9li1bkpxcaYYPERGRMuqpEhGRsOec4/3332f27Nm8/vrrFBUVMWrUKO6//34mTJhQVnQiLi4OoFL1v0mTJnkZvoiIhDglVSIiErZ27txJamoqTzzxBJ9//jnt27fnhhtu4Nprr6VPnz4Bt5k0aRKTJk0iPT2dxMTEhg1YREQaJSVVIiISVpxzrFq1itmzZ/PSSy+Rn5/PiBEjeO6555g4cSItWrTwOkQREQkzSqpERCQs7Nu3jxdffJHZs2fzySef0KpVKyZPnsx1113H4MGDvQ5PRELIggX1u/+f/7x+9y+hR0mViIg0auvWreOJJ54gNTWVPXv20L9/f/7+97/zy1/+kqOOOsrr8EREpAlQUiUiIo3OgQMHePXVV3niiSf44IMPaNasGRMnTuS6667jtNNOw8y8DlFERJoQJVUiIhKy0tLSKlTiu+mmm/j+++955plnyMnJoVevXtx33338+te/pmPHjl6HKyIiTZSSKhERCUlpaWkkJSWxf/9+ALKyspg2bRpmxoQJE7juuuv46U9/SkSEplwUERFvKakSEZGQ4pxj06ZN3HjjjWUJVXldu3bltdde8yAyERGRwJRUiYiI57Zs2cKSJUtYvHgxixcvJisrq8p1v/vuuwaMTERE5PCUVImISIPLyckhPT29LIn64osvAGjfvj1nnXUWf/jDH0hOTmbr1q2Vtu3Zs2dDhysiIlItJVUiIlLv9uzZw9KlS8uSqLVr1wLQunVrzjzzTK655hpGjRrFwIEDy56RateuXYVnqgBatmxJcnKyJ+cgIiJSFSVVIiJS5/bv38+HH35YlkStWrWK4uJimjdvzumnn85f/vIXRo0axdChQ4mOjg64j0mTJgFUqP6XnJxc1i4iIhIqlFSJiEiNHFrevHyCU1hYyMqVK8uSqOXLl1NYWEhUVBTDhw9nxowZjBo1ilNPPZWYmJgaH3PSpElKokREJOSFRFJlZt8AeUAxcNA5N9TMYoGXgXjgG2Cic26nf/0ZwFX+9W90zv3H3z4EeA5oASwEbnLOuYY8FxGRcBSovPnVV1/NggUL2LVrFx988AH79+/HzBg8eDA33ngjo0aN4owzzqBNmzYeRy8iIlK/QiKp8jvLOZdT7vN04D3n3D1mNt3/+RYz6wtcCvQDugLvmtkJzrliYDaQBHyEL6k6B1jUkCchIhKOZsyYUam8eUFBAS+//DJ9+/blyiuvZNSoUYwcOZLY2FiPohQREfFGKCVVhxoPJPp/fh5IB27xt7/knDsAbDKzjcBwf2/XUc655QBmlgpMQEmViEitlJSUsGHDBlasWFH2+vbbbwOua2asW7eugSMUEREJLaGSVDngbTNzwD+ccylAZ+fcVgDn3FYz6+Rftxu+nqhS2f62Iv/Ph7ZXYmZJ+Hq0iIqKIj09vQ5PJTzt3btX1ylM6F7Wn8Z6bXft2kVmZmbZ6/PPP2fv3r0AtGjRghNPPJGWLVsGnIi3U6dOjfKca6Kx3k+pTPcy9GVkdKjxugUF+WRkZNR4/TZtcoM63pEIdMymzsx6AKnAMUAJkOKcmxUuj/yESlJ1unPuO3/i9I6ZfV7NuhagzVXTXrnRl7SlALRq1colJibWMtymJz09HV2n8KB7WX8aw7UtKCjg008/rdALtWnTJgAiIiLo378/l112GSNGjGDEiBGcdNJJREZGVnqmCnzlzR944IGQP+cj1Rjup9SM7mXoy8ur+boZGRkkJCTUeP1At742xzsS+roFdBD4nXPuEzNrA6w2s3eAXxEGj/yERFLlnPvO/77dzF4HhgPbzKyLv5eqC7Ddv3o20KPc5t2B7/zt3QO0i4iEneoq8ZUqKSlh48aNFRKotWvXUlRUBED37t0ZMWIEU6dOZfjw4QwZMoTWrVsHPJ7Km4uISDD8I9BKR6HlmVkmvlFlYfHIj+dJlZm1AiL8F7cVMAa4C5gPXAHc43+f599kPvBPM3sQX9baG1jpnCs2szwzOwVYAUwBHm3YsxERqX+BKvElJSWRl5dHjx49yhKolStXsmvXLsA3ye7QoUOZNm1aWS9U165da3VclTcXEZFqRJnZqnKfU/yjwyoxs3hgML6/2evtkZ+G5HlSBXQGXjcz8MXzT+fcW2b2MTDXzK4CNgMXAzjn1pnZXGA9vm7E6/3dgABT+XF85SJUpEJEwtDMmTMrPd+0f/9+pk6dCvw4jO/iiy9mxIgRDB8+nL59+xIZGelFuCFjwYLarZ+R0aHGQ4R+/vPaxxNOantta6OpX1uRRuSgc27o4VYys9bAq8BvnXN7/DlAwFUDtNXqkZ+G5HlS5Zz7GhgYoD0XGF3FNslAcoD2VUD/uo5RRMQrzjm+/fZb1q5dy9q1a1mzZg1ZWVlVrp+enl7tMD4ROXJKHiUY9fn9gcbxHTKzaHwJVZpz7jV/c1g88uN5UiUiIj6FhYWsX7+eNWvWlCVQa9euZefOnWXrHH/88bRo0YL8/PxK28fFxTFy5MiGDFlERKRGzNcl9TSQ6Zx7sNyisHjkR0mViIgHcnJyKvQ+rV27lvXr13Pw4EHAV8o8ISGBiy++mIEDBzJo0CASEhJo06ZNlZX4kpMrdeCLx9SzISJS5nRgMpBhZmv8bbfiS6Ya/SM/SqpERIJUXSW+0gp85ZOnNWvWsGXLlrLtu3TpwqBBgxg7diyDBg1i4MCB9O7du8pnoFSJT0REGhvn3H8J/DwUhMEjP0qqRESCEKgS35VXXsmzzz7Lvn37yMjIYN++fQBERkZy0kknkZiYWJY8DRw4kE6dOlV3iIBUiU9ERCR0KKkSEamh/fv3s3nzZrKyssreH3744UqV+AoLC1m8eDFnnnkmV111Vdnwvb59+xITE+NR9CIiIlJflFSJSFipyaS4gTjnyMnJKUuWyidOpe85OTkVtomMjKS4uLiKPfoq8YmIBEPP5Yk0DkqqRCRsVDUpLsDEiRPZsmVLwGSp9OdDK+q1bNmSuLg44uLiGDp0KD179iQuLq7svWvXrhx//PEBS5z37Nmz/k9YJAD9ES4i0vCUVIlIo5afn09OTg45OTlMmzYt4KS4V1xxBVOmTKGkpKTCsk6dOhEXF0f//v0577zzKiRMPXv2JDY2lmomJQQgOTlZlfhERESaOCVVIlJvajsUr6ioiNzc3LIkqarXDz/8UPbzoUlUIMXFxdx2220VkqYePXrQokWLoM9RlfhEvFGbHrmMjA7k5dV8ffXIiUhtKakSkXoxZ84crr322rIhdaVV8RYsWECPHj0CJkq7d++ucn9HHXUUHTt2pGPHjhxzzDH079+fo48+uqytY8eOXHfddWzbtq3StnFxcdx11131dq6llfjS09NJTEyst+OIiIhIaFJSJdJEBFPAYd++feTm5lZ47dixo1Jb+deuXbsq7auwsJCXX36ZmJiYCgnRscceWyE5OjRZ6tChA82aNTtsrPv27dNQPBEREWlwSqpEmoBABRyuuuoqVq9eTf/+/Q+bJBUWFla57zZt2tChQ4eyV69evejQoQOPPfZYwPXNrFJBiLqioXiNh4opiIhIOFFSJeKBYHqNCgoK2LlzZ9lr165dh/28fv36SqW/Dxw4wEMPPVT2OSoqqkJydPzxxzNixIgKbeVfsbGxxMbGVtmDtGDBAk+q4mlSXBEREWloSqpEGlhVvUbp6emceOKJlRKjQ5Ok6nqNwNdz1L59e9q1a0f79u3p1asXGRkZAdc1M77++ms6dOhA69atD1vprjZUFU9EpHFST7JI7SmpEqlnzjm2bNnC2rVrWbNmDXfffXelinUHDhzgqaeeAiAiIqIsISpNjrp3714hUSq/rPzntm3bEhVV+dc6Pj6+yl6j+Pj4ejlvDcVrPPQHlIiISHCUVInUocLCQjIzM8sSqLVr17J27Vpyc3MPu62ZsWvXLlq3bk1ERESdxuVVr5GG4omIiEhToKRK5Ajl5uaWJU2lCdT69espKioCoEWLFiQkJPCLX/yCQYMGMXDgQBISEhgwYECVvUZHHXVUvcSqXiMRERGR+qOkSkLKkRZwqM9jlpSU8NVXX5UlTqXv2dnZZet06dKFQYMGce6553Lw4Lkcd9xxdOnShcjIyLJ1duyA99+HCy98jscee4zCwgNly5o1a86FF95w2GFYwQyl0lxKjYOG4omIiDQ+SqoakVBMOOr6WIcWcEhKSgJo0GNeddVVvPfeezRv3pw1a9aQkZHBvn37AIiMjOSkk04iMTGRgQMHlr06depUts/D/VFcmtDMmTOHH374gaOPPprJkycr0RERERFppJRUNRINmXA45ygpKeGFF15g6tSpZXMKZWVlcc0117Br1y7Gjx9PSUkJxcXF1b7XZJ3S95tvvrlSAYf9+/dz4403kpeXx8GDB8teRUVF1X6u6TofffQRBw4cqHDMAwcO8Oyzz9KuXTsGDhzI1VdfXZY89e3bl5iYmKCvcWJiopIoERERkTChpKqRmDlzZsCEIykpiVdffbVSsnC4V6AEo/yrKvn5+dxwww3ccMMN9X3KZXbs2MHUqVOrXB4VFUV0dDRRUVFlr5p+PjShKmVm7Nixo05LjIuIiIhIeAq7pMrMzgFmAZHAU865ezwOqU5s3rw5YPv+/fvZsGFDwMQhJiamwudAr0O3Kf+6/fbbq4wnJSWFyMhIIiIiDvtek3UiIyP5+c9/ztatWysdq1u3bqxatSpg3BEREUElPtWVGldCJSIiIiI1EVZJlZlFAn8HfgZkAx+b2Xzn3HpvIwtez549A/7xHxcXV+XErsF6+umnqzzmNddcU+fHu//++wOW/b733ns55phj6vx4oAlqpXq1LRqRkdGBvLyar6/CESIiIuGhbifD8d5wYKNz7mvnXCHwEjDe45jqRHJyMi1btqzQVt9//Df0MSdNmkRKSgpxcXGYGXFxcaSkpNRrMQ4vjikiIiIi4SWseqqAbsC35T5nAyMOXcnMkoAk8D2Pk56e3iDBBaNbt27cfPPNPPXUU2zfvp1OnTpx9dVX061bt3qL36tjPvfccxXa6vv+1PUxMzI6BBdQNdq0Ofwkwoezd+/eRvGdDwW1vZcFBfm16jkOdD+9+P7omIHV5n425vNsCsesi9/N2h6ztnTMhr2f9XmOoXRMaTjhllQFegjGVWpwLgVIAWjVqpVrLFXYEhMT+ctf/uLJMTW3Uc3VZvhXbdXFLdC9rLna3suMjAwSEhJqvH6g2+DF90fHDKw297Mxn2dTOGZd/G7W9pi1pWPWfB+h/m9tKB1TGk64JVXZQI9yn7sD33kUi0hY82KSWk2MKyIiIqEo3JKqj4HeZnYssAW4FLjc25BE6l9tkg0VUxARERGpW2GVVDnnDprZDcB/8JVUf8Y5t87jsEREREREJIyFW/U/nHMLnXMnOOd6OedUF1tEREREJASY2Tlm9oWZbTSz6V7HU5fCLqkSEREREZHQUm4+2XOBvsBlZtbX26jqTlgN/5Oaq89JTUPpGRwVNhAREREJCWXzyQKYWel8sus9jaqONPmkav/+/c7M8r2OoxGIAg424PEigeIGPF5T0tD30itefIeayrVtKnQ/w4cX91L/Has/TeV3s7F9h1qY2apyn1P80xiVqtF8so1Vk0+qnHMaAlkDZrbKOTe0AY+X4pxLaqjjNSUNfS+94sV3qKlc26ZC9zN8eHEv9d+x+tNUfjfD8DtUo/lkGyslFBKq6nHgnjQR+g6JiJf0b5AEK9y+Q2E9n6ySKglJzrlw+4dEGpi+QyLiJf0bJMEKw+9Q2XyyZtYM33yy8z2Oqc40+eF/UmMph19FGgndy/qjaxuX5VDWAAAgAElEQVRedD/Dh+5leNH9bITCfT5Zcy5shjKKiIiIiIg0OA3/ExERERERCYKSKhERERERkSAoqRIREREREQmCkioREREREZEgKKkSEREREREJgpIqERERERGRICipEhERERERCYKSKhERERERkSAoqRIREREREQmCkioREREREZEgKKkSEREREREJgpIqERERERGRICipEhERERERCYKSKhERERERkSAoqRIREREREQmCkioREREREZEgKKkSEREREREJgpIqERERERGRICipEhERERERCYKSKhERERERkSAoqRIREREREQmCkioREREREZEgKKkSEREREREJgpIqERERERGRICipEhERERERCYKSKhERERERkSAoqRIREREREQmCkioREREREZEgKKkSEREREREJgpIqERERERGRICipEhERERERCYKSKhERERERkSAoqRIREREREQmCkioREREREZEgKKkSEREREREJgpIqERERERGRICipEhERERERCYKSKhERERERkSAoqRIREREREQmCkioREREREZEgKKkSEREREREJgpIqERERERGRICipEhERERERCYKSKhERERERkSBEeR2A1zp27Oji4+O9DsMT+/bto1WrVl6HIfVE97dh6DqHN93f8Kb7G950fxvW6tWrc5xzR3sdh1eafFIVHx/PqlWrvA7DE+np6SQmJnodhtQT3d+Goesc3nR/w5vub3jT/W1YZpbldQxe0vA/ERERERGRICipEhERERERCYKSKhERERERkSA0+WeqAikqKiI7O5uCggKvQ6lXbdu2JTMz07Pjx8TE0L17d6Kjoz2LQUREREQkWEqqAsjOzqZNmzbEx8djZl6HU2/y8vJo06aNJ8d2zpGbm0t2djbHHnusJzGIiIiIiNQFDf8LoKCggA4dOoR1QuU1M6NDhw5h3xsoIiIiIuHP86TKzHqY2RIzyzSzdWZ2k7/9TjPbYmZr/K+x5baZYWYbzewLMzu7XPsQM8vwL3vEgsiKlFDVP11jERERkSB9Nhce6g93tvO9fzbX64iapFAY/ncQ+J1z7hMzawOsNrN3/Msecs79rfzKZtYXuBToB3QF3jWzE5xzxcBsIAn4CFgInAMsaqDzEBERERFpOJ/NhQU3QlG+7/Pub32fAQZM9C6uJsjznirn3Fbn3Cf+n/OATKBbNZuMB15yzh1wzm0CNgLDzawLcJRzbrlzzgGpwIR6Dh+ANz7dwun3LObY6W9y+j2LeePTLQ1xWBERERFpyt6768eEqlRRvq9dGlQo9FSVMbN4YDCwAjgduMHMpgCr8PVm7cSXcH1UbrNsf1uR/+dD2wMdJwlfjxadO3cmPT29wvK2bduSl5dXo5jf/N827nxzAwUHSwDYsiuf6a9+RkFBPuf171yjfXiluLi40nl26dKFrVu3Br3vtLQ0PvnkEx544IFq1ysoKKh0/aVu7N27V9e2Aeg6hzfd3/Cm+xvemsL9Hbk7m0APU7jd2bwf5uceakImqTKz1sCrwG+dc3vMbDbwZ8D53x8AroTA351q2is3OpcCpAAMHTrUJSYmVliemZlZVhXvTwvWsf67PVXG/enmXRQWl1RoKzhYwu3/3sDrn/0QcJu+XY/ijp/3q3KfDaWq6n91UREwJiaGZs2aHXZfMTExDB48OOjjSWXp6ekc+t2WuqfrHN50f8Ob7m94axL396O2ULCrUrO17R7+5x5iPB/+B2Bm0fgSqjTn3GsAzrltzrli51wJ8CQw3L96NtCj3Obdge/87d0DtNerQxOqw7XXRmpqKgMGDGDgwIFMnjyZX/3qV7zyyitly1u3bg34/tEYOXIkEydO5IQTTmD69OmkpaUxfPhwEhIS+Oqrr6o8xqZNmzj11FMZNmwYt912W4Vl999/P8OGDWPAgAHccccdZe0TJkxgyJAh9OvXj5SUlLL2Z599lhNOOIGRI0eybNmyoM9fRERERKqQswEO7AM75M/56BYw+nZvYmrCPO+p8lfoexrIdM49WK69i3OudBzaBcD//D/PB/5pZg/iK1TRG1jpnCs2szwzOwXf8MEpwKPBxne4HqXT71nMll35ldq7tWvBy9eeesTHXbduHcnJySxbtoyOHTuyY8cOpk2bVuX6a9euJTMzk9jYWI477jiuvvpqVq5cyaxZs3j00Ud5+OGHA2530003MXXqVKZMmcLf//73sva3336bDRs2sHLlSpxzjBs3jqVLl3LmmWfyzDPPEBsbS35+PsOGDePCCy+ksLCQO+64g9WrV9O2bVvOOuss9UCJiIiI1IfiIngtCWJaw1kzYdks2J0Nbbv7EioVqWhwnidV+J6dmgxkmNkaf9utwGVmNgjfEL5vgGsBnHPrzGwusB5f5cDr/ZX/AKYCzwEt8FX9q/fKf384uw8zXssgv6i4rK1FdCR/OLtPUPtdvHgxF110ER07dgQgNja22vWHDRtGly5dAOjVqxdjxowBICEhgSVLllS53bJly3j11VcBmDx5MrfccgvgS6refvvtssRo7969bNiwgTPPPJNHHnmE119/HYBvv/2WDRs28P3335OYmMjRRx8NwCWXXMKXX355pKcvIiIiIlX54AH47hO4+DnodwEMv8briJo8z5Mq59x/Cfw81MJqtkkGkgO0rwL61110hzdhsK8Wxv3/+YLvduXTtV0L/nB2n7L2I+WcqzSPU1RUFCUlJWXLCwsLy5Y1b9687OeIiIiyzxERERw8eLDaYwWaL8o5x4wZM7j22msrtKenp/Puu++yfPlyWrZsSWJiYtkEvpp3SkRERKSebVkN798HCRN9CZWEhJB4pqqxmzC4G8umj2LTPeexbPqooBMqgNGjRzN37lxyc3MB2LFjB/Hx8axevRqAefPmUVRUFPRxTj/9dF566SXAV7Gv1Nlnn80zzzzD3r17AdiyZQvbt29n9+7dtG/fnpYtW/L555/z0Ue+QowjRowgPT2d3NxcioqK+Ne//hV0bCIiIiJSTlE+vHYttDkGxt7vdTRSjuc9VRJYv379mDlzJiNHjiQyMpLBgwdz7733Mn78eIYPH87o0aNp1apV0MeZNWsWl19+ObNmzeLCCy8sax8zZgyZmZmceqrvubDWrVvzwgsvcM455/DEE08wYMAA+vTpwymnnAL4SrHfeeednHrqqXTp0oWTTz6Z4uLigMcUERERkSPw7p2QuwGmzIMW7byORsox3zy5TdfQoUPdqlWrKrRlZmZy0kkneRRRw6mqpHpDairX2gtNopRsCNB1Dm+6v+FN9ze8hd39/WoJzJkAI66Dc+/1OppKzGy1c26o13F4RcP/RERERERCWf4umHc9dOgNo+84/PrS4DT8r4lITk6u9JzTuHHjuOuuuzyKSERERERqZOEfIO97uPodaNbS62gkACVVTcTMmTOZOXNmhba8vDyPohERERGRGln3OmTMhcQZ0G2I19FIFTT8T0REREQkFOV9D/++GbqeDD/5ndfRSDWUVImIiIiIhBrnYN4NvjLqv0iByGivI5JqaPifiIiIiEioWf0sbHwHzr0POvb2Oho5DPVU1YXP5sJD/eHOdr73z+Z6HZGIiIiINFa5X8F/ZsJxiTDsGq+jkRpQUhWsz+bCghth97eA870vuFGJ1SHi4+PJycnxOgwRERGR0FZSDK9f5xvuN/5xiNCf642Bhv8dzqLp8H1G1cuzP4biAxXbivJ9Y2BXPx94m2MS4Nx76i5Gjxw8eJCoKH2FREREROrMsocheyX84ilo283raKSGlPoG69CE6nDttZCamsqAAQMYOHAgkydP5le/+hWvvPJK2fLWrVsDvhnDR44cycSJEznhhBOYPn06aWlpDB8+nISEBL766qsqj7Ft2zYuuOACBg4cyMCBA/nwww/55ptv6N+/f9k6f/vb37jzzjsBSExM5NZbb2XkyJHMmjWLH374gQsvvJBhw4YxbNgwli1bBkBubi5jxoxh8ODBXHvttTjngr4eIiIiImFt62ew5K/Q7wJIuMjraKQW1M1wOIfrUXqov3/o3yHa9oBfv3nEh123bh3JycksW7aMjh07smPHDqZNm1bl+mvXriUzM5PY2FiOO+44rr76alauXMmsWbN49NFHefjhhwNud+ONNzJy5Ehef/11iouL2bt3Lzt37qw2tl27dvH+++8DcPnll3PzzTdzxhlnsHnzZs4++2wyMzP505/+xBlnnMHtt9/Om2++SUpKyhFfCxEREZGwV1QAryVByw5w3oNg5nVEUgtKqoI1+nbfM1RF+T+2RbfwtQdh8eLFXHTRRXTs2BGA2NjYatcfNmwYXbp0AaBXr16MGTMGgISEBJYsWVLtcVJTUwGIjIykbdu2h02qLrnkkrKf3333XdavX1/2ec+ePeTl5bF06VJee+01AM477zzat29f7T5FREREmrTFf4YfMmHSK9Cy+r/7JPQoqQrWgIm+9/fugt3Z0La7L6EqbT9CzjnskP9DERUVRUlJSdnywsLCsmXNmzcv+zkiIqLsc0REBAcPHqzVscsfB6CgoKDC8latWpX9XFJSwvLly2nRokWl/Rwav4iIiIgE8M1/YfnfYeiV0PtnXkcjR0DPVNWFARPh5v/Bnbt870EmVACjR49m7ty55ObmArBjxw7i4+NZvXo1APPmzaOoqKhOjjN79mwAiouL2bNnD507d2b79u3k5uZy4MAB/v3vf1e5/ZgxY3jsscfKPq9ZswaAM888k7S0NAAWLVp02N4vERERkSapYA+8PhVij4Uxf/E6GjlCSqpCVL9+/Zg5cyYjR45k4MCBTJs2jWuuuYb333+f4cOHs2LFigo9Rkdq1qxZLFmyhISEBIYMGcK6deuIjo7m9ttvZ8SIEZx//vmceOKJVW7/yCOPsGrVKgYMGEDfvn154oknALjjjjtYunQpJ598Mm+//TY9e/YMOlYRERGRsPPWDNiTDRekQLPg/7YTb1hTr8o2dOhQt2rVqgptmZmZnHTSSR5F1HDy8vJo06aNpzE0lWvthfT0dBITE70OI+zpOoc33d/wpvsb3hrF/f38TXjpcvjJ72H0bV5HExQzW+2cG+p1HF5RT5WIiIiISEPb+wPMvxGOGQAjb/E6GgmSClU0EcnJyfzrX/+q0DZu3DjuuusujyISERERaaKcgwU3wYE8+EUKRDXzOiIJkpKqKgSqvteYzZw5k5kzZ1Zoy8vL8ygan6Y+9FRERESaqDVp8MWbMCYZOukxiHCg4X8BxMTEkJubqz/665FzjtzcXGJiYrwORURERKTh7MyCRdMh/idwym+8jkbqiHqqAujevTvZ2dn88MMPXodSrwoKCjxNamJiYujevbtnxxcRERFpUCXF8MZU388THocI9W+ECyVVAURHR3Psscd6HUa9S09PZ/DgwV6HISIiItI0LP87ZC2D8Y9DO003E06UHouIiIiI1Ldt62Dxn+HE82HQ5V5HI3VMSZWIiIiISH06WAivXQsxbeHnsyCMiqGJj4b/iYiIiIjUp/S/wrYMuOwlaNXR62ikHqinSkRERESkvmxeAcsehsGToc+5Xkcj9URJlYiIiIhIfTiwF15Pgrbd4ey7vY5G6pGG/4mIiIiI1Ie3Z/rmpfr1Qog5yutopB6pp0pEREREpK59+Tasfg5O+38Qd5rX0Ug9U1IlIiIiIlKX9uXC/BugUz8Y9X9eRyMNQMP/RERERETqinPw5s2wfwf88lWIau51RNIAlFSJiIiIiATrs7nw3l2w+1vf576/gGMSvI1JGoyG/4mIiIiIBOOzubDgxh8TKoANi3zt0iR4nlSZWQ8zW2JmmWa2zsxu8rfHmtk7ZrbB/96+3DYzzGyjmX1hZmeXax9iZhn+ZY+YabpqEREREaln790FRfkV24ryfe3SJHieVAEHgd85504CTgGuN7O+wHTgPedcb+A9/2f8yy4F+gHnAI+bWaR/X7OBJKC3/3VOQ56IiIiIiDQhOzbBR7Mr9lCVtzu7YeMRz3j+TJVzbiuw1f9znpllAt2A8UCif7XngXTgFn/7S865A8AmM9sIDDezb4CjnHPLAcwsFZgALGqwkxERERGR8FVSDFtWwxcL4Yu34IdMX3tEFJQcrLx+2+4NG594xvOkqjwziwcGAyuAzv6EC+fcVjPr5F+tG/BRuc2y/W1F/p8PbRcREREROTIH9sLXS+CLRfDlf2B/ji+JijsNTp4Cfc6B7FW+Z6rKDwGMbgGjb/cubmlQIZNUmVlr4FXgt865PdU8DhVogaumPdCxkvANE6Rz586kp6fXOt5wsHfv3iZ77k2B7m/D0HUOb7q/4U33N7wFc3+bF+TQIfdjOuR+TPudnxHhiiiKasWO2CHkxg1jR+zJHIxuDQeAzzYDneh0/FSO+3oOzQ/kcKB5R74+bjLbd3QCfceahJBIqswsGl9Cleace83fvM3Muvh7qboA2/3t2UCPcpt3B77zt3cP0F6Jcy4FSAEYOnSoS0xMrKtTaVTS09NpqufeFOj+Ngxd5/Cm+xvedH/DW63ub0kJbF0DX77l65H6/jNfe+xxMCIJ+pxLdM9T6BwZTecqd5II3AFADNDX/5KmwfOkyl+h72kg0zn3YLlF84ErgHv87/PKtf/TzB4EuuIrSLHSOVdsZnlmdgq+4YNTgEcb6DREREREpDEpyodNS33PR335H8jbChYBPUbAT/8EfcZCx96gYtJSA54nVcDpwGQgw8zW+NtuxZdMzTWzq4DNwMUAzrl1ZjYXWI+vcuD1zrli/3ZTgeeAFvgKVKhIhYiIiEhT4p+Ed+TubPi0u++5pgETfcvytsGG//h6o75aAgfzoVlrOH40nHAu9B4DrTp4G780Sp4nVc65/xL4eSiA0VVskwwkB2hfBfSvu+hEREREpNEonYS3KN/3x+Xub2H+DfD5m76ft6z2rde2B5w8GU44B+LPgKjmXkYtYcDzpEpEREREpE4EmoT34AFY/wZ0GwKj/s/XI9W5n4b1SZ1SUiUiIiIi4aHKyXYNrlncoKFI0xLhdQAiIiIiInXiqK6B2zUJr9QzJVUiIiIiEh46BShirkl4pQEoqRIRERGRxm/bOvhqMcT/BNr2wGG+ghQ/f+TH6n8i9UTPVImIiIhI41ZSAv+eBi3awcRUaBnL+5rcWRqQkioRERERadzWvgjffgTj/w4tY72ORpogDf8TERERkcZr/w545zbocQoMvNzraKSJUlIlIiIiIo3Xe3dB/i447wGI0J+24g1980RERESkccpeBaufgxHXwTH9vY5GmjAlVSIiIiLS+JQUw79vhjbHQOJ0r6ORJk6FKkRERESk8fn4afj+M7joWYg5yutopIlTT5WIiIiINC5522Dxn+G4s6DfBV5HI6KkSkREREQambf/Dw4WwNi/gZnX0YgoqRIRERGRRmTTUsiYC6f/Fjoe73U0IoCSKhERERFpLA4Wwpu/g3Zx8JNpXkcjUkaFKkRERESkcVj+GOR8CZf/C6JbeB2NSBn1VImIiIhI6Nu1Gd6/D048H04Y43U0IhUoqRIRERGR0Ldouq8oxTn3eB2JSCVKqkREREQktH2xCL54E0beAu16eB2NSCVKqkREREQkdBXuh0V/hKNPhFN+43U0IgGpUIWIiIiIhK4PHvA9T/WrNyGqmdfRiASknioRERERCU05G2DZLBhwKcSf4XU0IlVSUiUiIiIiocc535xU0S1hzJ+9jkakWhr+JyIiIiKh53+vwqb3YezfoHUnr6MRqZZ6qkREREQktBTshv/cCl0GwdArvY5G5LDUUyUiIiIioWXJX2HvdrjsRYiI9DoakcNST5WIiIiIhI6tn8HKf/h6qLoN8ToakRpRUiUiIiIioaGkxFecokUsjL7N62hEakzD/0REREQkNKx5AbJXwoTZ0KK919GI1Jh6qkRERETEe/ty4Z3boedpMPAyr6MRqRUlVSIiIiLivffuhII9cN4DYOZ1NCK1oqRKRERERLz17Ur4JBVO/Q107ut1NCK1pqRKRERERLxTfBD+PQ3adIWR072ORuSIqFCFiIiIiHjn4ydhWwZMTIXmrb2ORuSIqKdKRERERLyxZyssTobjfwonjfM6GpEjpqRKRERERLzx9kwoLoRz71NxCmnUQiKpMrNnzGy7mf2vXNudZrbFzNb4X2PLLZthZhvN7AszO7tc+xAzy/Ave8RMv50iIiIiIemrJfC/V+En06BDL6+jEQlKSCRVwHPAOQHaH3LODfK/FgKYWV/gUqCff5vHzSzSv/5sIAno7X8F2qeIiIiIeOngAVj4e2h/LJz+W6+jEQlaSCRVzrmlwI4arj4eeMk5d8A5twnYCAw3sy7AUc655c45B6QCE+onYhERERE5Yh8+ArkbYezfIDrG62hEghbq1f9uMLMpwCrgd865nUA34KNy62T724r8Px/aXomZJeHr0aJz586kp6fXfeSNwN69e5vsuTcFur8NQ9c5vOn+hjfdX2/E5G9j2Mf3kXv0aazfEgVb0uvlOLq/0pBCOamaDfwZcP73B4ArgUDPSblq2is3OpcCpAAMHTrUJSYm1kG4jU96ejpN9dybAt3fhqHrHN50f8Ob7q8HnIN/XgKR0XT65VN0ahvw/3/XCd1faUghMfwvEOfcNudcsXOuBHgSGO5flA30KLdqd+A7f3v3AO0iIiIiEgq+WAgb/gNnzYB6TKhEGlrIJlX+Z6RKXQCUVgacD1xqZs3N7Fh8BSlWOue2Anlmdoq/6t8UYF6DBi0iIiIigRXug0W3QKe+MOI6r6MRqVMhMfzPzF4EEoGOZpYN3AEkmtkgfEP4vgGuBXDOrTOzucB64CBwvXOu2L+rqfgqCbYAFvlfIiIiIuK1pffD7m/h129BZLTX0YjUqZBIqpxzlwVofrqa9ZOB5ADtq4D+dRiaiIiIiARr++fw4aMwaBLEnep1NCJ1LmSH/4mIiIhIGHDONydVs9bws7u8jkakXoRET5WIiIiIhKmMf8E3H8D5D0Grjl5HI1IvlFSJiIiISN37bC68eyfs2QKRzSC6pdcRidQbJVUi/7+9+46Po77zP/76bpG0sqoty2o2btjERbjRIdg49ByQkDik/xLuSCeEC+0SCHEuBEI6OS7hyF1IBYdQTAsEE5NQAy7IDWMbN0m2Zdnqdcv398eMpJW1ctNKu1q9n4/HPHZ3Znbmu/O1Vnr7O/MZERERia+KZfDEtRBsc16HO+HJ68B4oHxJYtsmMgjiek2VMWbF0cwTERERkRRlLTz7Hz2BqkuwDVbomipJTXEZqTLGZACZOCXR8wHjLsoBSuKxDxERERFJYu2NUPEQvHE/tOyPvU5D5dC2SWSIxOv0v88B1+EEqFX0hKpG4L/itA8RERERSTY1m5wg9daD0NkMxXMgkA9tdX3XzS0b+vaJDIG4hCpr7U+BnxpjvmKtvSce2xQRERGRJBUOwttPwhu/cir7edNg5gfh1H+D0vlOxb/oa6oA/AFYfFvi2iwyiOJaqMJae48x5kxgYvS2rbW/ied+RERERCQBmvbCql87U9MeyJ0A77sd5n6yd7n0rmIUK5Y6p/zlljmBSkUqJEXFNVQZY34LTAHWAmF3tgUUqkRERESGI2th58vwz/9xRqciIZiy2Lnv1IkXgMcb+33lSxSiZMSId0n1BcAMa62N83ZFREREZCh1NLmFJ34FNRshIxdO+zws+CyMmZLo1okklXiHqvVAEbAnztsVERERkaFQ83ZU4YkmKCqHy+6BWR+CNN3AVySWeIeqAmCjMeafQEfXTGvtZXHej4iIiIjESzgEm59yTvHrLjzxATjlX6HsFDDmyNsQGcHiHapuj/P2RERERGSwNO2FVQ+4hSeqIXe8U1Bi7qcga2yiWycybMS7+t+L8dyeiIiIiAxQxbK+Vfhyy5xRqU3L3cIT58GlP4RpF/ZfeEJE+hXv6n9NONX+ANIAP9Birc2J535ERERE5ChULOt9v6iG3fDINYCF9Fw49RpYcDUUTE1oM0WGu3iPVGVHvzbGXAGcGs99iIiIiMhRWrG09w14AbAQyIevbYC0UQlplkiq8Qzmxq21jwHnDeY+RERERCSGcMgZmYqlrV6BSiSO4n363wejXnpw7lule1aJiIiIDKUdL8PTN/S/PLds6NoiMgLEu/rfv0Q9DwE7gMvjvA8RERERiaWxGv56G6z7k1PJ77TPw+oHep8C6A84xSpEJG7ifU3VZ+K5PRERERE5CqFOeO1eePH7TjW/c2+Cs65zbtZbOr9v9b/yJYlusUhKiffpf2XAPcBZOKf9vQR81VpbGc/9iIiIiIhr6/PwzE1wYCtMvwQuvANGT+pZXr5EIUpkkMW7UMX/AcuBEqAUeMKdJyIiIiLxVLcDHvw4/O5KsBY+/jB89I+9A5WIDIl4X1M11lobHaJ+bYy5Ls77EBERERm5gm3w8k/hpR+D8cDib8EZXwJfeqJbJjJixTtU1RpjPgH80X39UeBAnPchIiIiMvJYC28/Bc/eAvW7YNaVcP53ILc00S0TGfHiHao+C/wc+DHONVWvACpeISIiIjIQtVuc66a2rYDCGfDpJ2HSOYlulSSBx9ZUcfezm6mub6MkL8ANF07nirkK2kMt3qHqO8CnrbV1AMaY0cAPcMKWiIiIiByLjib4+93w6r1OKfSL7oJT/hW88f4TToajx9ZUccsj62gLhgGoqm/jlkfWAShYDbF4/0SWdwUqAGvtQWPM3DjvQ0RERCS1WQvrHoa/3gpNe2DOJ+B934KswkS3TJLIHU9v6g5UXdqCYe5+drNC1RCLd6jyGGPyDxmp0n+liIiIiBytvevh6Rtg1ytQPAeW/BbGn5LoVkkSsNaycU8jf1m/l2fW76WmqSPmetX1bTHny+CJd+D5IfCKMeZhnGuqlgDfjfM+RERERFJPWx387Q54437IyIN/+SnM/SR4vCwm9jAAACAASURBVIlumSRQJGJ5q7K+O0jtOtiKx8ApE0ezP+CjoS3U5z0leYEEtHRki2uostb+xhjzJnAeYIAPWms3xnMfIiIiIiklEoE1v4UV33aC1YKrYdF/QOboRLdMEiQcsbyx4yB/Wb+Xv6zfy97Gdnwew5lTC/jCwimcP2McBVnpfa6pAgj4vdxw4fQEtn5kivupeW6IUpASEREROZLKVfD016F6NYw/HS65G4rLE90qSYBgOMIr2w7wl/V7+evGvdQ2d5Lm83DutLHcOGs6i08aR26mv9d7uq6bUvW/xNP1TiIiIiJDoWIZrFgKDZWQUwz5k2Dny5A1Dj5wH5QvAWMS3UoZQu3BMP/YUssz6/fw/MZ9NLaHyEzzsuikQi6eVcSi6YWMSj/8n+tXzC1ViEoCClUiIiIig61iGTxxLQTdAgKN1c504gVw5a8gIyex7UshXfdtqqpvo/S1F5Ju5KalI8TfNtfwzPq9rHy7hpbOMDkZPt43YxwXzyrmnBMLyPDrOrrhRqFKREREZLCtWNoTqKLVbFKgiqNkvW9TQ2uQFW/v45n1e/n7O/vpCEUYMyqNy+aUctGsIs6YPIY0nydh7ZOBU6gSERERGSzWwpa/QsPu2MsbKoe2PSnu7mffjnnfplseWceqnXVkZ/jICfidxwx/9+uc7td+MvwezHGchtk1QtZ1bdMXFk7G6/HwzPq9vLK1llDEUpSTwUdPncBFs4o4ZeJovB6d7pkqkiJUGWP+F3g/UGOtneXOGw08BEwEdgBLou5/dQtwNRAGrrXWPuvOnw/8GggATwNftdbaofwsIiIiIlgL215wSqRXvQnGCzbcd73csqFvW4ra19hOVX17zGVtwTBPVlTT2B4iHDn8n4Z+ryE745DgFRXAYr1etbOOn7+wlY5QBHBGyL752AYAJozO5OqzJ3HRrCJOLsvDoyCVkpIiVOEEoZ8Dv4madzOwwlp7pzHmZvf1TcaYGcBVwEygBHjeGDPNWhsG/hu4BngNJ1RdBDwzZJ9CRERERjZrYfvfnTC1+zXIHe/cb8qbDk99rfcpgP4ALL4tcW1NEdZalr25m/98alO/65TmBXj55vOw1tIWDNPYFqKpPUhje5DG9hCNbUGa2kM0tjuPTe3BqHVCvFvb3P26pTNGOO7H2Ox0Xrxh4XGNfMnwkhShylr7d2PMxENmXw4sdJ8/AKwEbnLnP2it7QC2G2O2AqcaY3YAOdbaVwGMMb8BrkChSkRERIbCjpedMLXzJcgugUt/6Ny815fuLPd4e6r/5ZY5gap8SWLbPMztPtjKLY+s46WttZw6cTTnzxjHj/76Tr/3bTLGkJnmIzPNR1FuxnHtMxSO0NwRorEt5IayIB/7n9djrlvb1KFANUKYZDk7zg1VT0ad/ldvrc2LWl5nrc03xvwceM1a+zt3/q9wgtMO4E5r7fvc+ecAN1lr3x9jX9fgjGgxbty4+Q8++OBgfrSk1dzcTFZWVqKbIYNE/Ts0dJxTm/o3tcWrf3MaNjFp+x/Ir6+gIy2fXRM+xJ7iC4h40+LQSoklYi0rdoV4+J1ODPDh6WksGu/DYwyvVAf58ztBDrRHGJPh4cppfs4s8R9xmwPx7ytbOdDe92/qMRmGHy7MHNR9J4tFixatstYuSHQ7EiUpRqqOUay4bw8zv+9Ma+8D7gNYsGCBXbhwYdwaN5ysXLmSkfrZRwL179DQcU5t6t/UNuD+rXzTGZnatgJGjYUL7yB9wWc50R/gxLi1Ug61bX8zNz1cwZs7W3nvtLHc8YFZlOX3BJeFwH8wtD+/t+b2rjoIzgjZrZfPZmESlXOXwZPMoWqfMabYWrvHGFMM1LjzK4HxUeuVAdXu/LIY80VERETip3oN/O17sOVZCIyG85fCKf8KaaMS3bKUFgpHuO8f7/KT57eQ4fPwgw+fzJXzSpPi9Lqucu3R1f+S7f5YMriSOVQtBz4N3Ok+Ph41/w/GmB/hFKo4EfintTZsjGkyxpwOvA58Crhn6JstIiIiKWlPBay8EzY/BRl5zjVRp14D6dmJblnK21jdyI1/fov1VY1cNLOIpVfMpDD7+K6JGixXzC1ViBrBkiJUGWP+iDNaW2CMqQS+hROmlhljrgZ2AR8GsNZuMMYsAzYCIeBLbuU/gC/QU1L9GVSkQkRERAZq30ZY+T3YtBzSc2HRN+C0z+umvUOgIxTmv17Yyr0rt5GX6efej8/jktnFiW6WSB9JEaqstR/tZ9Hiftb/LvDdGPPfBGbFsWkiIiIyUu3f7IxMbXgU0rLg3Jvg9C9CIO/I75UBW7OrjhsfrmBLTTMfmFvKbe+fQf4oFf+Q5JQUoUpEREQkadRuhRfvgnV/An8mnHM9nPFlyByd6JaNCG2dYX743Gb+9+XtjMvJ4P/+3yksOqkw0c0SOSyFKhERERGAg+/Ci3dDxYPgy4CzroUzr4VRBYlu2Yjx2rsHuOnPFew80MrHTpvALRefRHbG4JZDF4kHhSoREREZWSqWwYqlnNtQCWvKnFP6ajbC2j+A1++8PuurkKXRkaHS1B7kzmfe5vev72LC6Ez+8G+nceYUhVkZPhSqREREZOSoWAZPXAvBNucGlw274dlbwHjh1H+Ds78G2UWJbuWI8rfNNXzjkXXsaWzn6rMn8e8XTCMzTX+iyvCif7EiIiIycqxYCsG2vvOzCuHiu4a+PSNYfWsnS5/YyCNrqphamMWfv3Am8ybkJ7pZIsdFoUpERERSX2erU8WvYXfs5U17h7Y9I9wz6/Zw6+MbqG/t5CvnTeXL500l3edNdLNEjptClYiIiKSuPRWw+gGo+BN0NIDHB5FQ3/Vyy4a+bSNQTVM733p8A8+s38us0hwe+OwpzCzJTXSzRAZMoUpERERSS0cTrP8zrHoAqleDNx1mXgHzPg2NVd3XVHXzB2DxbYlrb4p6bE0Vdz+7mer6NkryMjh32lieWreXtmCYGy+azjXnTMbn9SS6mSJxoVAlIiIiw5+1ToBa9YATqDqboXAGXHQXlC/pe4+pFUuxDZWY3DInUJUvSUy7U9Rja6q45ZF1tAXDAFTVt/OHf+5m4phM/vzpM5lamJXgForEl0KViIiIDF/tDU5Fv9UPwN51zs16Z34Q5n8ayk4BY/q+p3wJlC/hxZUrWbhw4ZA3eSS4+9nN3YEqWmc4okAlKUmhSkRERIYXa2H3P50gtf4RCLVB0Wy49Icw+8OQoWt0hlpHKMyG6kbW7Kpnza46qupjVFgE9tS3D3HLRIaGQpWIiIgMD60HoeIh5xS//ZsgLQtO/ohzrVTJ3NijUhJ31lp2H2xjze46J0TtrmdjdQPBsAWgNC9AwO+hLRjp896SvMBQN1dkSChUiYiISPKyFna+7ASpjY9DuANK58O//AxmXQnpOpVssDW1B6mobGDNrjrW7q5nza56DrR0AhDweykvy+Xqsyczd0Iec8fnUZiT0eeaqq51b7hweqI+hsigUqgSERGR5NNSC2v/AKt/Awe2QHouzPuUc61U0exEty5lhSOWLTVNrN1V745C1bGlphnrDEIxtTCLRScVugEqn2njsmJW8LtibilAVPW/ADdcOL17vkiqUagSERGRxKhYBiuWQkOlc5+o826FrELnWqlNT0IkCONPh3P+HWZcDmmZiW7xsNS7tHnvcLO/qYO1u+tZ657K99buelo6ndGlvEw/c8fncensEuZOyOPk8XnkBvxHvd8r5pYqRMmIoVAlIiIiQ69iWe/7RTXshkc/B1gI5MOp/+ZcK1V4UkKbOdz1LW3exg0Pv8UDr+ygtqWD3Qed4+/zGN5TnMOV88uYMz6PuRPymTgmE6Pr1ESOikKViIiIDL0VS3vfgBdwAtUYuH4j+DMS0qxUEQpH2La/hduf2NCntHkwbHmrsp6LZhXxqdMnMmdCHrNKcgmkeRPUWpHhT6FKREREhlao0xmZiqXtoALVMQpHLNtrm6mobGBdVQPrKhvYUN0Y8z5RXayFez8+fwhbKZLaFKpERERk6Ox4GZ78Wv/Lc8uGri3DUCRi2XmwlYrKetZVNlBR1cCGqobu66ACfi8zS3K46tTxlJfl8r2n36amqaPPdlTaXCS+FKpERERk8LUcgL/eCmt/D3kT4Ixr4c3/6X0KoD8Ai29LXBuTTNf9oCqq3ABV2cD6qgaaOkIApPs8zCjJ4UPzy5hdlsfs0lymjB3Vqxqfwai0ucgQUKgSERGRwWMtrPmdE6g6muDsr8F7b3Qq+RXP7l39b/FtUL4k0S0eNIerwmetpaq+rXv0aX2VE6Ia2oIApHk9vKc4m8vnljC7NJfZpXmcOC4Lf4xy5tFU2lxkaChUiYiIyOCoeds51W/XK05p9Pf/GMbN6FleviSlQ1S0WFX4bnz4LZ5eV01HyLKuqoGD7g11fR7D9KJsLpldxOzSPMrLcpk2Lps03+EDVH9U2lxk8ClUiYiISHx1tsI/fgAv/wzSs+Cye2DOJ8BzfKFguGtqD/KfT23sUziiM2x5bmMNJxVl8773FDK7LI/y0lymF2WT4VclPpHhRKFKRERE4mfL8/DU9VC/E07+GFzwHRhVkOhWDZlIxPJubTOrd9WzZpdzQ93N+5qwNvb6BvjLde8d0jaKSPwpVImIiMjANe6BZ2+BDY/CmBPh00/CpHMS3apB19AaZG1lPat31rFmdz1rd9XR2O4UksjJ8DFnQj4XzSrit6/u5IB7el80VeETSQ0KVSIiInL8ImF441fwwncg1AGLvglnXQu+9ES3LO7CEcuWmibW7OoJUVtrmgEwBqaPy+bS8mLmTshn3oQ8Jhdk4fEYACaOGaUqfCIpTKFKREREjk/1WnjyOqheA1POg0t+AGOmJLpVcVPX0sma3c4pfKt31fHW7gaa3XLm+Zl+5k7I5/KTS5h3Qj7lZblkZ/j73Zaq8ImkNoUqEREROTbtjfC3O+Cfv4TMArjyVzDrSme4ZhjoKm1eVd9G6WsvcMOF03l/eTGb9zX1uhZqe20LAB4DJxXlcMXcEuaOz2feCflMHJOJOcbPqyp8IqlLoUpERESOjrWwaTk8cxM07YVTrobzboVAXqJbdtRilTa/ftlabnj4LYJhp5pEQVYac8bn8+EFZcwd74xCjUrXn0wi0j99Q4iIiMiR1e2Ep78OW56Dotnwkd9B2YJEt+qIrLXsPtjGhuoGNlQ38j//eJeOUKTXOhELAa+HH3x4NnPH5zN+dOCYR6FEZGRTqBIREZH+hYPw6s9h5V1gPHDhHXDq58CbfH9CBMMRttY0s6G6sTtEbapupMm9DsrrMYQjsWubt3aGuXyOTs0TkeOTfN+IIiIikhx2vQZPXAf7N8FJ74eL74LcskS3CoCWjhCb9jSycU8jG6oa2bCngXf2NtMZdkahMvweTirK4bI5JcwsyWVmSQ7Ti7JZ/MMXqapv67M9lTYXkYFQqBIREZHeWg/C89+C1b+B3PFw1R/hpEvivpuughFHqoZX29zRPfq0sbqRjdWNbD/Q0n1D3fxMPzNLcvnMWROZUZLDzJIcJhVk4fX0PYXvhgunq7S5iMSdQpWIiMhIV7EMViyFhkoI5Dv3mwq1w5lfgXNvhvSsuO8yVsGIWx6p4EBzByV5gZ4QtaeRfY0d3e8rzQswsySHy+eUMrMkhxklORTnZhz1NVDRpc2r6tsoVWlzEYkDhSoREZGRrGIZPHEtBN1T4toOOtdOnXcrnHP9oO32+8++3Wu0CKAtGOE7T20CnOufpo7N4swpBd3haWZxLrmZ/d8L6mh1lTZfuXIlCxcuHPD2REQUqkREREai9gbY8TI8+bWeQNXFRuDN/41bqIpELO/WtrCuqp6KygbWVzVQXd/e7/qPf+ksphdlk+H3xmX/IiKDLelDlTFmB9AEhIGQtXaBMWY08BAwEdgBLLHW1rnr3wJc7a5/rbX22QQ0W0REJLmEOmD3P+HdlbD9RahaDTbc//oNlce1G2stOw+0UlHVwLpKJ0RtqG6k2a3Al+H3MLMkl1HpXlo6+u6/NC/AyeOHz32vRERgGIQq1yJrbW3U65uBFdbaO40xN7uvbzLGzACuAmYCJcDzxphp1h7ut4aIiEgKioRhbwW8+6ITpHa9BqE2MF4oneeMQk06Fx77fOwAdRRV/qy1VNa1UVHZQEVVPesqG1hX1UBTuxOg0nweZhTn8MF5pcwuzaW8LI8pY0fh83r6XFMFKhghIsPXcAlVh7ocWOg+fwBYCdzkzn/QWtsBbDfGbAVOBV5NQBtFRESGjrVwYBtsX+kEqe1/h/Z6Z9nY98D8T8PkhXDCmZCR2/O+xd8i9PhX8IV7TscLeTPwLb7tkM1bqhvaWVdZz7qqBircAFXfGgTA7zW8pziHy04uobwsl1mluUwbl43f64nZ3OiCEUeq/icikuyMtbFvgpcsjDHbgTrAAr+01t5njKm31uZFrVNnrc03xvwceM1a+zt3/q+AZ6y1Dx+yzWuAawDGjRs3/8EHHxyqj5NUmpubycqKf0UnSQ7q36Gh45zakr1/0zoOkl9XQV79W+TXvUVGxwEA2tMLqMs/mbr8curzyulMH93vNl6pDlK78QWu9yyjxByg2o7hR5ElBE5cREHAw/aGCDsaImxvDNPU6bzHa6As28MJOR4m5XiYlOuhNNuDP0YJ82SW7P0rA6P+HVqLFi1aZa1dkOh2JMpwGKk6y1pbbYwpBP5qjHn7MOvG+jbvkxqttfcB9wEsWLDAjtTKP6p6lNrUv0NDxzm1JV3/tjfAjpfckagXYb/7KzGQD1Pe65zON3khGaMnU2wMxUexyW/cuYKq0Nk8wtm9F2xyRqC8HsOJhVlcNDuX8rJcZpflcVKKFJFIuv6VuFL/ylBK+lBlra12H2uMMY/inM63zxhTbK3dY4wpBmrc1SuB8VFvLwOqh7TBIiIixyv6flG5ZbDwFudx+4tOkKpe7VTm8wXghDNgzsecIFVUDp7Yp9lFs9ay+2Ab66sb2FDdwPqqRqoOU4Xvz184kxnFOQTShn+AEhEZTEkdqowxowCPtbbJfX4BsBRYDnwauNN9fNx9y3LgD8aYH+EUqjgR+OeQN1xERORYHXq/qIbd8PgXnefGC6Xz4Zx/d66LKjsFfOmH3VwoHOHd2pbu8LSh2qnC11VEwucxTC3MIjPNS2tn7Cp880/Ij+MHFBFJXUkdqoBxwKPuXdJ9wB+stX8xxrwBLDPGXA3sAj4MYK3dYIxZBmwEQsCXVPlPRESSVqgTqtfAzpfhxbsgFGPUKLMArl0DGTn9bqYjFOadvc29RqDe3ttIezACQLrP011EYlZpLjNLcpg2zjmFT1X4REQGLqlDlbX2XeDkGPMPAIv7ec93ge8OctNERESOXbAdqt50brq782XnvlGhtsO/p/VAr0DV3BFi055GNlQ1sL66kQ3VjWzZ10Qo4lxCnJ3uY0ZJDh8/7QRmluQwqzSXyQVOGfNYVIVPRGTgkjpUiYiIDGudLU5w2vmyE6Sq3oRwJ2Bg3EyY9ymYeBZMOJPW/zqHzLY9fTbRkDaOP764jQ3VTpDafqCFrsK9Y0alMbM0l0XTxzKzJJdZpTmMz8/Ec4xV+K6YW6oQJSIyAApVIiIi8dLeCLtfdyr07XzZObUvEgLjgeKT4dRr4ISzYMLpkNlT5rw9GOZ7HUu4xf43maaze36rTePW5g+y/Jm3Kc0LMLMkh8vnlDKrNIeZJbmMy0nHPUVeREQSSKFKRETkeLUehF2vws5XnCC1t8KpzufxQck8OPMrTogafxpk5HCwpZOtNc1sW9/Mtpq9bNvfzNb9zVTWtWHtaTR4gtzo67lf1PdDS1geOZs1t55P/qi0RH9aERHph0KViIjIodzS5uc2VMKaMlh8G5Qvgeb9zgjUzlecx30bAAvedChbAOd8nfCEs6jKmsnW+gjbalrY+lYz255fz7b9zdS1Brt3ke7zMHlsFieX5fHBuWX85tUdLG89m+Wdve8XVZoXUKASEUlyClUiIiLRKpYRevwr+MLtzh3lG3YTefTzeJ67FZr3Ouv4MwmXnkLt/OvZEjiZVaFJvHMgxNa3mtn+QgudoZ67eYwZlcaUsVlcNKuYKWNHMaUwi6ljsyjNC/S69mlSwShV4RMRGaYUqkRERAA6mmBPBZ1P/Dtp4d6lzT02TGfLQV4s+QKvhKbzQkMJO98O9Sw3u5kwOpMpY7M4d/pYpowdxdTCLCYXZB31KJOq8ImIDF8KVSIiMvIE22HfeqhaDdWriVStxtS+g8HSXwTyRYJcu3shUwpHMXdSFh8am8WUwiymjM3ihDGZZPi9A26WqvCJiAxPClUiIpLawkGo2USochWt29+A6jVkNbyDxzojTQfJZU14MhWRD/KWncz3fL+i2HOwz2aq7Rg2fPvCYy5XLiIiqU+hSkREktZja6qO6XS4SChE7a4NNGx9nXDlarIOrKOw9R3SbCc+wNpMKiKTqbCXsM0/jabRs8kuPIHJY7OYVpDFhQWj+MWvgtwUurdPafP70z7B7QpUIiISg0KViIgkpcfWVPHSo/fyEA9Skl5LdWsBP3n0KuCLnDttLO/ub6Zm12aCu98ksL+CcU0bmRLaSqFppxBoselsYhKvZ1xCQ/5sIkVzyC+bzqTCLD42ZlS/1zrNff813PZoiOvsg92lzX/CVZx96TVD+vlFRGT4UKgSEZGktObJ+1hq7useMSoztXzX/oKVj7zKOjqZ7dnOfNMMQCc+KtOmsnH0pQSL5hCYuICiyeXMyx3FgmMcXXJGwr7IR55dTFV9G6UqGCEiIkegUCUiIgnTHgyz40ALO2pb2F7b6jweaKFyfz2Phf6v1yl4AOkmxAWeVRzMnkZb4cWEJywgd+pppBXNZLIvjclxaldXwYiVK1eycOHCOG1VRERSlUKViIgMqo5QmN0HW3uFph21zlTd4JQuz6KVeZ4tvDd9G5/0v8O08GbSTEfM7VljGPP1N4byI4iIiByWQpWIiBzRkQpGBMMRKuva3BGnFnYc6HmsqmsjYnu2lZ/pZ25+B58r2MqcMZuY2FJBTuNmjI0AHhhTDidcTcfqP5LeWdenLe2BIjKH4DOLiIgcLYUqERE5rMfWVHHLI+toC4YBqKpv44aH3+KR1ZV4PYYdB1rZfbCVUFRyys7wMalgFHPH5/OBOaWUZ+xnWuc6iurXklb1OhzY7qzoz4SyBTDnMphwhvM8PRuA9JK5hB7/Cr6oG/GGvBlkXrx06D68iIjIUVCoEhERAELhCPuaOqg82EplXRuVdW1U1bfy+NpqOkKRXusGw5Z/bKnlPcU5zCjO4ZLZRUwqyGJSQSYT89IY3fQ2ZtdrsOtVWPsqtB5w3pg5xglPp/yr81hcDl5/7AaVL3F+Sa1YCg2VkFuGb/FtUL5kUI+DiIjIsVKoEhEZRo71vk3RguEIexva3cDUOzhV1rWxp6GdcPR5esC4nHQ6QhEu87zEjb5llJhaqm0B3w8t4YnI2Tz91XOgoxkq33AC1PpXofJNCLY6G8ifCCdeCBNOhxPOhDFTwRxDNb7yJQpRIiKS9BSqRESGiVin4d3yyDrAqVbXGYqwp8ENSn2CUxt7Gnpf22QMFOVkUJoXYMEJ+ZTlZ1KWH6A0P0BZfibFuRlk+L3c/p/f4sbg/b1Km9/tv4+Pel6F++6GPRVgw2A8MG4WzP0knHAGjD8dcoqH/DiJiIgMNYUqEZFhIBKx3PmXt7sDVZe2YJgbH67gzmfeZl9TOzYqNHkMFOcGKM0LcNqk0ZS5YckJTQGKcwOk+Tz97zQcgtqt3OJ5gPQYpc1Pt2vAfzacc70zElV2KmTkxPNji4iIDAsKVSIix6HrNLyq+jZKX3vhuG8O2xmKsL+5g5rGdvY3dVDjTvubol43dlDb3NGrEESvbYQjnDW1wA1Nge4Rp6LcDPzew4SmLsE2qN0Cte/A/s1Quxn2vwMHt0G4k/R+3mYw8Jmnjvkzi4iIpBqFKhGRY3Sk0/CstbR0hqlpbI8KSR3UNLWzv7ErODmhqa412Gf7xsCYUWmMzc5gbHY608ZlU5idzu9f30lDW6jP+qV5AX645OQjN7ytzglLtZvd8OSGqPpdgBvYjMe5DqpgOky7wHlccTs01/TdXm7ZUR4xERGR1KZQJSJylKy11LcGuePpTf2ehvfj59+hprGjz3KANK+HsdnpjM1OZ+KYUZw6aTRjszIozEmnMDudQjdEjclKiznCNG1cNi89ei/X8WB3wYifcBVnX/jF6EZC096e0aauALV/M7REBSNvOhScCKXzYc7HoGAajJ0Oo6eAP6P3jr1+eOJaZ0Sriz8Ai287ruMoIiKSahSqRGRYG0g1vC5dYWlfUzv7Gjt6Rpga3dfu/P1NHXSGI/1upzMcobwszw1I6RTmpPcKTbkBP+ZYKt8d4grvy7zff3/3fZvKTC13eX6Jd2s17Az0jD51NPa8KT3HCUwnnu+EpoLpMHYa5J0AHu/R7bir+l5UaXNU2lxERKSbQpWIDFtHcxpeXWuwOxTtc69b2tfYTk1jB/uanMf+wlJOho9xOU4oOm3SaMbmpDMuO4N7XtgS87S90rwA93x0bvw/aDgENRvhmRt73QgXwBsJwoZHIGucE57Kl/QEp4LpkF10bCXM+6PS5iIiIv1SqBKRYaczFOFASwff7ec0vBsefou7n93cb1jKDfgpzE5nXE4Gp00aRWFORvfrQjc4Feakk+GPPZIzelRarzAHEPB7ueHC6QP/cNbCwXehajVUrYLq1U7J8lDbYd5k4OvvDHzfIiIiclwUqkQkLgZ6Gl5HKMyB5k5qm52Ro9rmDmqbO7ufR89raOs7ShQtGLacNnk0hdkZjMtJ7/V4uLB0tLo+V3f1v+M87RCAxj1OcKpa5QSp6tXQ3uAs8wWg+GRY8Bnn2qfnvglNe/puQwUjREREEkqhSkQGrL/T8ELhCGdMLaA2RjDa39xBBYstUAAAEyBJREFUbVNH92Nje9+qdgDZ6T4KstMpyEpjelE2Z2WlU+BOP3huMwdbOvu8pzQvwI+WzBnUz3zF3FKumFvKypUrWbhw4dG9qa0eqte4I1DuY1dIMl4YNwNmXOEEqNJ5MPY94I36mrYRFYwQERFJQgpVIikmXvdPOpS1lsb2EHUtndS1ulNLkLrWTn7y/JaYp+F9/eGKmNvKzvAx1g1GJxVlUzC1wHmd3RWY0ijIcqrkHW5UKTPNe+RqeIOlYhmsWMq5DZWwJkbhhmCbc9pe9eqeU/kObutZPnoKTDzbCVAl86BoNqRlHn6fKhghIiKSlBSqRFLIkQo3dAlHLPWtndS1Bt1w1El9a5CDbliqb3Ged6/T0kl9W5BwPzefPZw7PzjbCUrZPWFpoKffdYlVDe9O7/34vCcDgxg0KpZ1jxgZgIbdsPzLsP3vTkW9qlVQswki7uhbdnFP6fLSeVAyFwL5x7dvFYwQERFJOgpVIoMkHqW+DyccsTR3hGhqD9LUHqK5I8R3ntwYc8Topj9X8MCrO9xRpiCN7UFsP/kozeshf5Sf/Mw08jL9TBuXRV5mGvmZzrz8zLTu5V3TxT/7O9X17X22VZoX4KpTJ8TtM/ex4tt9quH5wu3wzE0Q6nBOl7MRsGGnAISNQCR8yHz3eSTSz/yo93bNf+uPvU/BA2d/a34LGbnOyNNZX3UeS+dBTsngHQMRERFJOIUqkUFwpBGjjlCYpvaQE4banWDU6D46QanneWN71Ouo5y2dfW8u25+OUISsdB9l+ZlR4chP/qi0PkEpM817zPdSuvHCkwa3Gl7THjiw1Z229TxvqIz9nraDzsjRcTFgPM7k8fY8N16nNLnxQGdL/++9aWd8SpiLiIjIsKFQJSlvMEaMguEIjW1BGg6Zuub94sVtMUeMrl+2lhsfrjjsDWS7BPxesjJ8ZGf4yM7wk53uoygno/t1VrqzLCfD373e9Q+9xf7mjj7bKs0L8NurTxvQZz6c6Gp4x32cWw/2DkxdAergNgi29qznC8DoyVA4A5r3QUdT321lF8PVz0WFoeiQZPqZ3xWejiIQ/XiWc8rfoXLLFKhERERGIIUqSWmHGzG6tLy431DU0No3MEUvP5pRoss8L3Gjb1l3AYXvh5awPHI2nzl7IjkZfjcc+chK73me7T7PyvDh93qO+fN+49L3JKxwwxXel7kifSlkVEJ6GXhvo891TZ0tzj2YukecokJU28Ge9YwX8k+AMVNh0jkwZorzfMxUyC4Bj3tsoq5t6uYPwPlLIW8QTztcfJuq8ImIiEg3haoRaLCqwx3JG8t/yfjVd1No91NjxrJ73g2cctnnjnk71lragxGaO5zriJrbQzR1OKfGdc3rusboN6/s4Pzwi9yY1jvcfO2hMNc9tPaw+wn4veQG/N1TWX4muSX+qHk+cjP95AXSyIlaLyfg43t3LuXG4P1kGqfcd5mp5U7//Yz2p3HLxZce1/E7GslQuAFwRnEe/xJseQ7Ss3tCVGNV7/dllziBacblPaFpzFQnEPnSjrzfRFXDi9qvbajEqAqfiIjIiKZQlUhuSeah/GPwsTVVvPTovTzEg5Sk11LdWsBPHr0K+OKgBatwxPLG8l9w8prbCJhOMFDEfnJXfZPHG1rxnXwVzR1BmjvCbjAK9gpGXWGpKSo0HU0VOr/XcLH9B3f6+4YbgjB18Wd7haboYJQb8JPmNU6RgkioZ7KR3q8jnRBp63ndFIaGMDd7f0dGqPf9kzJNJ7d4HoC33gPhIESCzmM4COFO5/3hzp550csjwaNYFoIDW/BFet/vyRduh0c/B8/dGr9OPVRLjXNsooU7Yd2fICMPCk6ESe91yoh3jTqNngzpWQPfd6Kq4bn7ffFY7lMlIiIiKUmhKlEqlhF6/Cs9lcsadjuvYcB/IAbDEVo7w7R2hpzHjjAtnSHaOsO8/vgvWGru6xUyltr7uP0xw6bqq4gEO7ChDiKhIDbcAaEghDuwIecPdxPphJD7GAniCQcxkU48kSCeSCeeSAiPDeIJd+IjiDcSxEeYj3lXOIEqSsB0cv7WO3jhnb8wCks2FoPF76F78nmM+wh+L/iyLL4cg89YfB7wGfB6wGssXtP70QMEqyvw0ztkZJpOfpT2C3wVTxwSkMK9Q5Q9+kIQh8roZ356Z50TcPplwOsHbxp4fM6j1+9MHv8hz9Oc0RxvVs+y/Ztib9ZGYNqFx/15jmj1A/0sMHDzzsHbr4iIiEgSUKhKkNZnbiMzRino8KNfoG3F97GRCBFrsRYiNoKNWKw9dIq4j84pcRBxHx0GSwBLJlDgvn4v9XhN71GeTNPJXfYezBv3xO8Dupe8hL1ewiYNf7hvuW2AAJ2cP2Y/Ho8Hj/Hg8Xgw3QUDcB6jq7EZ4xYCiH7t7qzXa+fRd0ig6uIl4oyceLxOePH4nOt4ol93T4fOj7GO8fR+/fgXoWV/3x1nFcFnno4KTlFByZvmbHsg+i2gMB4u+9nAtn04217ov3CDiIiISIpLuVBljLkI+CngBe631t6Z4CbFlNG2N+Z8TyTEPw7muWM2YJ1bi2IweLwevB6Dz+OED6/HgzdqXtdrn8eD1+vO83rweb3d8zzvPBS7QQZY9A33j/v0nj/yu0ZKfOlRoyZpMaaukZP0XoHB6/HgBfbePpUi+oaMfWYsRdetjs9BjfWx+gkZJnc8XHHvoO2XC++IXcjggu84p78NlkQVUFDhBhERERnBUipUGWO8wH8B5wOVwBvGmOXW2o2JbVlf1ZExlHlq+8yvsgUUX/Mwo9K8BNK8jErzkZnuJc3rOeZ7B8XSetffyWzb02d+W6CYzHNvHPD2+7N73g3krvpmr1MA22wau+ffQNGg7ZXE/bE/0gooJOrzioiIiCSBlApVwKnAVmvtuwDGmAeBy4GkC1X3p32CG4P3dl/bBNBq07g/7RPcPj5v0PabefHS3tdyASFvBpkXLx20fQKcctnneAPc6n+11JgCds8/vup/xySRf+yPtAIKifq8IiIiIglmoq/BGe6MMR8CLrLW/qv7+pPAadbaLx+y3jXANQDjxo2b/+CDDw55W1+pDlK78QWu9yyjxByg2o7hR5ElFMw4jzNL/IO678J9LzL53d+S3rGfjvSxvDv5k9SMO3dQ9ylDr7m5maysOFTXk8PScU5t6t/Upv5NberfobVo0aJV1toFiW5HoqTaSFWs8+P6pEZr7X3AfQALFiywiSiHvBB4bM0MPvLs+VTXt1GSFxiy+0U5e/8WK92RjBnAjCHYqwytlSr1PSR0nFOb+je1qX9Tm/pXhlKqhapKYHzU6zKgOkFtOaIr5pYOUYgSEREREZHB4kl0A+LsDeBEY8wkY0wacBWwPMFtEhERERGRFJZSI1XW2pAx5svAszgl1f/XWrshwc0SEREREZEUllKhCsBa+zTwdKLbISIiIiIiI0Oqnf4nIiIiIiIypBSqREREREREBkChSkREREREZABS6ua/x8MYsx/Ymeh2JEgBUJvoRsigUf8ODR3n1Kb+TW3q39Sm/h1aJ1hrxya6EYky4kPVSGaMeXMk3/k61al/h4aOc2pT/6Y29W9qU//KUNLpfyIiIiIiIgOgUCUiIiIiIjIAClUj232JboAMKvXv0NBxTm3q39Sm/k1t6l8ZMrqmSkREREREZAA0UiUiIiIiIjIAClUiIiIiIiIDoFCVRIwx440xfzPGbDLGbDDGfNWdP9oY81djzBb3Md+df74xZpUxZp37eF7Utua787caY35mjDH97DPmesaY9xpjVhtjQsaYDx2mzdcbYzYaYyqMMSuMMSdELQsbY9a60/J4HafhKgX79y5jzHp3+ki8jtNAJNkx7vfYHfL+dGPMQ+77XzfGTIxa9hdjTL0x5sn4HaXhKwX7V9+RUVKwf5PuOzKRhmn/xvxdaYw5wW3TWvezfD6ex0qGKWutpiSZgGJgnvs8G3gHmAF8H7jZnX8zcJf7fC5Q4j6fBVRFbeufwBmAAZ4BLu5nnzHXAyYC5cBvgA8dps2LgEz3+ReAh6KWNSf6mCbTlEr9C1wK/BXwAaOAN4EcHeNex7jfn41D3v9F4Bfu86sO+RlaDPwL8GSij20yTCnYv/qOTNH+JUm/I9W/x9y/E4nxuxJIA9Ld51nAjq62ahq5U8IboOkwnQOPA+cDm4Fid14xsDnGugY4AKS767wdteyjwC9jvOeI6wG/5jB/dB+y7lzg5ajX+oMhRfsXuAH4ZtSyXwFLEn1Mk/EYH3rsYix7FjjDfe4DanGLCLnzFqJQlZL9q+/I1O3f4fIdqf49fP9GrfNr+vldCYwBdqFQNeInnf6XpNxTCOYCrwPjrLV7ANzHwhhvuRJYY63tAEqByqhlle68Qx3tekfrapz/CeqSYYx50xjzmjHmigFsN+WkQP++BVxsjMk0xhTg/K/f+AFsO+6S7Bgf+rNx6DZ2u20LAQ04v6TlMFKkf/Ud2Y8U6N+k/45MpGHUv/1yT2eswOn/u6y11ce6DUktvkQ3QPoyxmQBfwaus9Y29nOqcPT6M4G7gAu6ZsVYzcZ661Gud0TGmE8AC4Bzo2ZPsNZWG2MmAy8YY9ZZa7cdz/ZTSSr0r7X2OWPMKcArwH7gVSB0PNseDMl0jPv52TimbUhvKdS/+o6MIRX6N9m/IxNpmPVvv6y1u4FyY0wJ8Jgx5mFr7b5j3Y6kDo1UJRljjB/ny+b31tpH3Nn7jDHF7vJioCZq/TLgUeBTUb+MK4GyqM2WAdXGGK/puSh6aX/rHaF93+3aRtS89wHfAC5z/xcJgK7/tbHWvgusxPlfqREtxfr3u9baOdba83F+eW05+iMxeJLpGMc6djGOcSXu/2AbY3xALnBwoMchVaVS/+o7sq8U69+k/I5MpGHYv0fk/hxvAM452vdIikr0+YeaeiacL93fAD85ZP7d9L6I8/vu8zycUwyujLGtN4DT6bk485J+9nnY9TjCNTc4fwRsA048ZH4+PRdxFuD8MpmR6GOs/o1b/3qBMe7zcmA94NMx7lmvv2MX4/1foveF7ssOWb4QXVOVcv2r78iU79+k/I5U/x5b/0Zt59f0LlRRBgTc5/k4RTdmJ/oYa0rslPAGaIrqDDgbZ2i6AljrTpfgnJ+9wv2luwIY7a7/TaAlat21QKG7bIH7Jb4N+DlRF74fss+Y6wGn4PwvTwvOxaEb+nn/88C+qP0vd+efCaxzvxDXAVcn+vgmekqx/s0ANrrTa8CcRB/fJDzGMY9djPdnAH8CtuJUqpoctewfOKcOtbn9dWGij7H6Nz79i74jU71/k/I7Uv17zP0b83clToGNCvfntwK4JtHHV1Pip65/XCIiIiIiInIcdE2ViIiIiIjIAChUiYiIiIiIDIBClYiIiIiIyAAoVImIiIiIiAyAQpWIiIiIiMgAKFSJiIiIiIgMgEKViIgMCWPMDmNMwRHW+Y847ev/GWN+foR1FhpjzozH/kREZGRTqBIRkWQSl1B1lBbi3IRXRERkQBSqRETkqBhjJhpj1ke9/rox5nZjzEpjzE+MMa8YY9YbY051l48xxjxnjFljjPklYKLe+5gxZpUxZoMx5hp33p1AwBiz1hjze3feJ4wx/3Tn/dIY4z1M+z5jjHnHGPMicFbU/H8xxrzutuN5Y8w4Y8xE4PPA19xtn2OMGWuM+bMx5g13OqufXYmIiPSiUCUiIvEwylp7JvBF4H/ded8CXrLWzgWWAxOi1v+stXY+sAC41hgzxlp7M9BmrZ1jrf24MeY9wEeAs6y1c4Aw8PFYOzfGFAPfxglT5wMzoha/BJzutuNB4EZr7Q7gF8CP3f39A/ip+/oU4Erg/gEeExERGSF8iW6AiIikhD8CWGv/bozJMcbkAe8FPujOf8oYUxe1/rXGmA+4z8cDJwIHDtnmYmA+8IYxBiAA1PSz/9OAldba/QDGmIeAae6yMuAhN3ilAdv72cb7gBnuvgByjDHZ1tqmw35yEREZ8RSqRETkaIXofYZDRtRze8i6tp/5GGMW4gSYM6y1rcaYlYdsq3tV4AFr7S1H2b4++3LdA/zIWrvc3fft/azncdvUdpT7ExERAXT6n4iIHL19QKF7rVQ68P6oZR8BMMacDTRYaxuAv+OermeMuRjId9fNBercQHUScHrUdoLGGL/7fAXwIWNMobuN0caYE/pp2+vAQrdtfuDDUctygSr3+aej5jcB2VGvnwO+3PXCGDOnn32JiIj0olAlIiJHxVobBJbiBJgngbejFtcZY17BuU7panfet4H3GmNWAxcAu9z5fwF8xpgK4DvAa1HbuQ+oMMb83lq7Efgm8Jy77l+B4n7atgdnBOpV4HlgddTi24E/GWP+AdRGzX8C+EBXoQrgWmCBMabCGLMRp5CFiIjIERlr+ztbQkRE5Mjc0/e+bq19M9FtERERSQSNVImIiIiIiAyARqpERGRYMca8DqQfMvuT1tp1iWiPiIiIQpWIiIiIiMgA6PQ/ERERERGRAVCoEhERERERGQCFKhERERERkQFQqBIRERERERmA/w8eY3BjbIorrwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 936x720 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = utils.tsplot_conf_dead_cured(daily_frm[daily_frm['city_name_en'] == 'Wuhan'], logy=False, title='Confirmed, Dead, and Cured Counts in Wuhan')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cross-sectional plot examples:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = utils.cross_sectional_bar(daily_frm, '2020-02-03', col='cum_confirmed', groupby='province_name', \n",
    "                                title='2020-02-03 Confirmed Count comparison among all provinces')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Use the *largestN* parameter to show only the top N bars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = utils.cross_sectional_bar(daily_frm, '2020-02-05', col='new_confirmed', groupby='city_name_en', largestN=10, \n",
    "                                title='Top 10 cities with the most new confirmed counts on 2020-02-05')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cum_confirmed</th>\n",
       "      <th>cum_cured</th>\n",
       "      <th>cum_dead</th>\n",
       "      <th>new_confirmed</th>\n",
       "      <th>new_cured</th>\n",
       "      <th>new_dead</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>update_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-02-09</th>\n",
       "      <td>27100</td>\n",
       "      <td>1480</td>\n",
       "      <td>780</td>\n",
       "      <td>2147.0</td>\n",
       "      <td>262.0</td>\n",
       "      <td>81.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-10</th>\n",
       "      <td>29631</td>\n",
       "      <td>1854</td>\n",
       "      <td>871</td>\n",
       "      <td>2531.0</td>\n",
       "      <td>374.0</td>\n",
       "      <td>91.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-11</th>\n",
       "      <td>31728</td>\n",
       "      <td>2310</td>\n",
       "      <td>974</td>\n",
       "      <td>2097.0</td>\n",
       "      <td>456.0</td>\n",
       "      <td>103.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-12</th>\n",
       "      <td>33366</td>\n",
       "      <td>2686</td>\n",
       "      <td>1068</td>\n",
       "      <td>1638.0</td>\n",
       "      <td>376.0</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-13</th>\n",
       "      <td>48206</td>\n",
       "      <td>3459</td>\n",
       "      <td>1310</td>\n",
       "      <td>14840.0</td>\n",
       "      <td>773.0</td>\n",
       "      <td>242.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-14</th>\n",
       "      <td>51986</td>\n",
       "      <td>3900</td>\n",
       "      <td>1318</td>\n",
       "      <td>3780.0</td>\n",
       "      <td>441.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-15</th>\n",
       "      <td>54406</td>\n",
       "      <td>4774</td>\n",
       "      <td>1457</td>\n",
       "      <td>2420.0</td>\n",
       "      <td>874.0</td>\n",
       "      <td>139.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             cum_confirmed  cum_cured  cum_dead  new_confirmed  new_cured  \\\n",
       "update_date                                                                 \n",
       "2020-02-09           27100       1480       780         2147.0      262.0   \n",
       "2020-02-10           29631       1854       871         2531.0      374.0   \n",
       "2020-02-11           31728       2310       974         2097.0      456.0   \n",
       "2020-02-12           33366       2686      1068         1638.0      376.0   \n",
       "2020-02-13           48206       3459      1310        14840.0      773.0   \n",
       "2020-02-14           51986       3900      1318         3780.0      441.0   \n",
       "2020-02-15           54406       4774      1457         2420.0      874.0   \n",
       "\n",
       "             new_dead  \n",
       "update_date            \n",
       "2020-02-09       81.0  \n",
       "2020-02-10       91.0  \n",
       "2020-02-11      103.0  \n",
       "2020-02-12       94.0  \n",
       "2020-02-13      242.0  \n",
       "2020-02-14        8.0  \n",
       "2020-02-15      139.0  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# answer to Q1\n",
    "daily_frm[daily_frm['province_name_en'] == 'Hubei'].groupby('update_date').agg('sum')[-7:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x17f94ddfb70>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = daily_frm[daily_frm['province_name_en'] == 'Hubei'].groupby('update_date').agg('sum')[-8:-1].copy()\n",
    "x.plot(y='cum_confirmed', figsize=(14, 10), marker='o', grid=True, title='Hubei Province Confirmed Count in the Past 7 Days')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# answer to Q2\n",
    "frm1 = daily_frm[(daily_frm['province_name_en'] == 'Guangdong') | (daily_frm['province_name_en'] == 'Zhejiang')].copy()\n",
    "frm1['update_date'] = pd.to_datetime(frm1['update_date'])\n",
    "frm2 = frm1.groupby(['update_date', 'province_name_en']).agg('sum')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x17f94d5e780>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = frm2['new_confirmed'][:, 'Guangdong'].plot(figsize=(15,10), label='Guangdong', grid=True, marker='*')\n",
    "frm2['new_confirmed'][:, 'Zhejiang'].plot(ax=ax, label='Zhejiang', grid=True, title='New Confirmed Comparison', marker='o')\n",
    "ax.legend(loc='upper right')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "daily_frm[(daily_frm['update_date'] == pd.to_datetime('2020-02-13'))].sort_values('cum_dead', ascending=False)[:5].to_csv('Q3A.csv', encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub_frm['fatality_rate'] = sub_frm['cum_dead'] / sub_frm['cum_confirmed']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>update_date</th>\n",
       "      <th>province_name</th>\n",
       "      <th>province_name_en</th>\n",
       "      <th>city_name</th>\n",
       "      <th>city_name_en</th>\n",
       "      <th>cum_confirmed</th>\n",
       "      <th>cum_cured</th>\n",
       "      <th>cum_dead</th>\n",
       "      <th>new_confirmed</th>\n",
       "      <th>new_cured</th>\n",
       "      <th>new_dead</th>\n",
       "      <th>update_time</th>\n",
       "      <th>fatality_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1835</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>仙桃</td>\n",
       "      <td>Xiantao</td>\n",
       "      <td>480</td>\n",
       "      <td>48</td>\n",
       "      <td>16</td>\n",
       "      <td>20.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.033333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1823</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>武汉</td>\n",
       "      <td>Wuhan</td>\n",
       "      <td>32994</td>\n",
       "      <td>1923</td>\n",
       "      <td>1036</td>\n",
       "      <td>13436.0</td>\n",
       "      <td>543.0</td>\n",
       "      <td>216.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.031400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1829</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>鄂州</td>\n",
       "      <td>Ezhou</td>\n",
       "      <td>1065</td>\n",
       "      <td>97</td>\n",
       "      <td>30</td>\n",
       "      <td>204.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.028169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1836</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>天门</td>\n",
       "      <td>tianmen</td>\n",
       "      <td>362</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.027624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1965</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>安徽省</td>\n",
       "      <td>Anhui</td>\n",
       "      <td>蚌埠</td>\n",
       "      <td>Bengbu</td>\n",
       "      <td>146</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2020-02-13 21:29:32.534</td>\n",
       "      <td>0.027397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1830</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>荆门</td>\n",
       "      <td>Jingmen</td>\n",
       "      <td>927</td>\n",
       "      <td>93</td>\n",
       "      <td>24</td>\n",
       "      <td>231.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.025890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1825</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>黄冈</td>\n",
       "      <td>Huanggang</td>\n",
       "      <td>2662</td>\n",
       "      <td>427</td>\n",
       "      <td>58</td>\n",
       "      <td>264.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.021788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1837</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>恩施州</td>\n",
       "      <td>Enshizhou</td>\n",
       "      <td>229</td>\n",
       "      <td>48</td>\n",
       "      <td>4</td>\n",
       "      <td>26.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.017467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1824</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>孝感</td>\n",
       "      <td>Xiaogan</td>\n",
       "      <td>2874</td>\n",
       "      <td>209</td>\n",
       "      <td>49</td>\n",
       "      <td>123.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.017049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1826</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>荆州</td>\n",
       "      <td>Jingzhou</td>\n",
       "      <td>1431</td>\n",
       "      <td>104</td>\n",
       "      <td>23</td>\n",
       "      <td>321.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.016073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1792</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>河南省</td>\n",
       "      <td>Henan</td>\n",
       "      <td>南阳</td>\n",
       "      <td>Nanyang</td>\n",
       "      <td>145</td>\n",
       "      <td>38</td>\n",
       "      <td>2</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 22:47:24.225</td>\n",
       "      <td>0.013793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1832</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>宜昌</td>\n",
       "      <td>Yichang</td>\n",
       "      <td>810</td>\n",
       "      <td>72</td>\n",
       "      <td>11</td>\n",
       "      <td>26.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.013580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1834</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>咸宁</td>\n",
       "      <td>Xianning</td>\n",
       "      <td>534</td>\n",
       "      <td>85</td>\n",
       "      <td>7</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.013109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1827</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>随州</td>\n",
       "      <td>Suizhou</td>\n",
       "      <td>1160</td>\n",
       "      <td>62</td>\n",
       "      <td>14</td>\n",
       "      <td>31.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.012069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1828</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>襄阳</td>\n",
       "      <td>Xiangyang</td>\n",
       "      <td>1101</td>\n",
       "      <td>66</td>\n",
       "      <td>13</td>\n",
       "      <td>13.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.011807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2220</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>上海市</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>外地来沪人员</td>\n",
       "      <td>Non_Residence</td>\n",
       "      <td>101</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 20:39:00.939</td>\n",
       "      <td>0.009901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1831</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>黄石</td>\n",
       "      <td>Huangshi</td>\n",
       "      <td>911</td>\n",
       "      <td>115</td>\n",
       "      <td>9</td>\n",
       "      <td>37.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.009879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1851</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>重庆市</td>\n",
       "      <td>Chongqing</td>\n",
       "      <td>万州区</td>\n",
       "      <td>Wanzhouqu</td>\n",
       "      <td>103</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.009709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>四川省</td>\n",
       "      <td>Sichuan</td>\n",
       "      <td>成都</td>\n",
       "      <td>Chengdu</td>\n",
       "      <td>131</td>\n",
       "      <td>42</td>\n",
       "      <td>1</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 21:29:32.534</td>\n",
       "      <td>0.007634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2107</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>Hunan</td>\n",
       "      <td>岳阳</td>\n",
       "      <td>Yueyang</td>\n",
       "      <td>148</td>\n",
       "      <td>42</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 20:39:00.939</td>\n",
       "      <td>0.006757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2187</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>Helongjiang</td>\n",
       "      <td>哈尔滨</td>\n",
       "      <td>Ha_erbin</td>\n",
       "      <td>159</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2020-02-13 20:39:00.939</td>\n",
       "      <td>0.006289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1966</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>安徽省</td>\n",
       "      <td>Anhui</td>\n",
       "      <td>合肥</td>\n",
       "      <td>Hefei</td>\n",
       "      <td>161</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 21:29:32.534</td>\n",
       "      <td>0.006211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1833</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>十堰</td>\n",
       "      <td>Shiyan</td>\n",
       "      <td>562</td>\n",
       "      <td>81</td>\n",
       "      <td>1</td>\n",
       "      <td>26.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.001779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1925</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>深圳</td>\n",
       "      <td>Shenzhen</td>\n",
       "      <td>391</td>\n",
       "      <td>94</td>\n",
       "      <td>0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 21:29:32.534</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2261</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>陕西省</td>\n",
       "      <td>Shanxi</td>\n",
       "      <td>西安</td>\n",
       "      <td>Xi_an</td>\n",
       "      <td>114</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 20:39:00.939</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2106</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>Hunan</td>\n",
       "      <td>长沙</td>\n",
       "      <td>Changsha</td>\n",
       "      <td>228</td>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 20:39:00.939</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1967</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>安徽省</td>\n",
       "      <td>Anhui</td>\n",
       "      <td>阜阳</td>\n",
       "      <td>Fuyang</td>\n",
       "      <td>142</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 21:29:32.534</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1926</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>广州</td>\n",
       "      <td>Guangzhou</td>\n",
       "      <td>327</td>\n",
       "      <td>78</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 21:29:32.534</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1841</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>宁波</td>\n",
       "      <td>Ningbo</td>\n",
       "      <td>153</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2095</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>江西省</td>\n",
       "      <td>Jiangxi</td>\n",
       "      <td>上饶</td>\n",
       "      <td>Shangrao</td>\n",
       "      <td>119</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 20:39:00.939</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1842</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>杭州</td>\n",
       "      <td>Hangzhou</td>\n",
       "      <td>162</td>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2094</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>江西省</td>\n",
       "      <td>Jiangxi</td>\n",
       "      <td>南昌</td>\n",
       "      <td>Nanchang</td>\n",
       "      <td>210</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 20:39:00.939</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2097</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>江西省</td>\n",
       "      <td>Jiangxi</td>\n",
       "      <td>新余</td>\n",
       "      <td>Xinyu</td>\n",
       "      <td>121</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 20:39:00.939</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1791</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>河南省</td>\n",
       "      <td>Henan</td>\n",
       "      <td>信阳</td>\n",
       "      <td>Xinyang</td>\n",
       "      <td>240</td>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 22:47:24.225</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1794</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>河南省</td>\n",
       "      <td>Henan</td>\n",
       "      <td>郑州</td>\n",
       "      <td>Zhengzhou</td>\n",
       "      <td>141</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 22:47:24.225</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1793</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>河南省</td>\n",
       "      <td>Henan</td>\n",
       "      <td>驻马店</td>\n",
       "      <td>Zhumadian</td>\n",
       "      <td>134</td>\n",
       "      <td>42</td>\n",
       "      <td>0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 22:47:24.225</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1843</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>台州</td>\n",
       "      <td>Taizhou</td>\n",
       "      <td>144</td>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1840</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>温州</td>\n",
       "      <td>Wenzhou</td>\n",
       "      <td>490</td>\n",
       "      <td>140</td>\n",
       "      <td>0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2096</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>江西省</td>\n",
       "      <td>Jiangxi</td>\n",
       "      <td>九江</td>\n",
       "      <td>Jiujiang</td>\n",
       "      <td>109</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020-02-13 20:39:00.939</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     update_date province_name province_name_en city_name   city_name_en  \\\n",
       "1835  2020-02-13           湖北省            Hubei        仙桃        Xiantao   \n",
       "1823  2020-02-13           湖北省            Hubei        武汉          Wuhan   \n",
       "1829  2020-02-13           湖北省            Hubei        鄂州          Ezhou   \n",
       "1836  2020-02-13           湖北省            Hubei        天门        tianmen   \n",
       "1965  2020-02-13           安徽省            Anhui        蚌埠         Bengbu   \n",
       "1830  2020-02-13           湖北省            Hubei        荆门        Jingmen   \n",
       "1825  2020-02-13           湖北省            Hubei        黄冈      Huanggang   \n",
       "1837  2020-02-13           湖北省            Hubei       恩施州      Enshizhou   \n",
       "1824  2020-02-13           湖北省            Hubei        孝感        Xiaogan   \n",
       "1826  2020-02-13           湖北省            Hubei        荆州       Jingzhou   \n",
       "1792  2020-02-13           河南省            Henan        南阳        Nanyang   \n",
       "1832  2020-02-13           湖北省            Hubei        宜昌        Yichang   \n",
       "1834  2020-02-13           湖北省            Hubei        咸宁       Xianning   \n",
       "1827  2020-02-13           湖北省            Hubei        随州        Suizhou   \n",
       "1828  2020-02-13           湖北省            Hubei        襄阳      Xiangyang   \n",
       "2220  2020-02-13           上海市         Shanghai    外地来沪人员  Non_Residence   \n",
       "1831  2020-02-13           湖北省            Hubei        黄石       Huangshi   \n",
       "1851  2020-02-13           重庆市        Chongqing       万州区      Wanzhouqu   \n",
       "1996  2020-02-13           四川省          Sichuan        成都        Chengdu   \n",
       "2107  2020-02-13           湖南省            Hunan        岳阳        Yueyang   \n",
       "2187  2020-02-13          黑龙江省      Helongjiang       哈尔滨       Ha_erbin   \n",
       "1966  2020-02-13           安徽省            Anhui        合肥          Hefei   \n",
       "1833  2020-02-13           湖北省            Hubei        十堰         Shiyan   \n",
       "1925  2020-02-13           广东省        Guangdong        深圳       Shenzhen   \n",
       "2261  2020-02-13           陕西省           Shanxi        西安          Xi_an   \n",
       "2106  2020-02-13           湖南省            Hunan        长沙       Changsha   \n",
       "1967  2020-02-13           安徽省            Anhui        阜阳         Fuyang   \n",
       "1926  2020-02-13           广东省        Guangdong        广州      Guangzhou   \n",
       "1841  2020-02-13           浙江省         Zhejiang        宁波         Ningbo   \n",
       "2095  2020-02-13           江西省          Jiangxi        上饶       Shangrao   \n",
       "1842  2020-02-13           浙江省         Zhejiang        杭州       Hangzhou   \n",
       "2094  2020-02-13           江西省          Jiangxi        南昌       Nanchang   \n",
       "2097  2020-02-13           江西省          Jiangxi        新余          Xinyu   \n",
       "1791  2020-02-13           河南省            Henan        信阳        Xinyang   \n",
       "1794  2020-02-13           河南省            Henan        郑州      Zhengzhou   \n",
       "1793  2020-02-13           河南省            Henan       驻马店      Zhumadian   \n",
       "1843  2020-02-13           浙江省         Zhejiang        台州        Taizhou   \n",
       "1840  2020-02-13           浙江省         Zhejiang        温州        Wenzhou   \n",
       "2096  2020-02-13           江西省          Jiangxi        九江       Jiujiang   \n",
       "\n",
       "      cum_confirmed  cum_cured  cum_dead  new_confirmed  new_cured  new_dead  \\\n",
       "1835            480         48        16           20.0        5.0       3.0   \n",
       "1823          32994       1923      1036        13436.0      543.0     216.0   \n",
       "1829           1065         97        30          204.0       25.0       2.0   \n",
       "1836            362         13        10           69.0        1.0       0.0   \n",
       "1965            146          3         4            5.0        1.0       1.0   \n",
       "1830            927         93        24          231.0        9.0       0.0   \n",
       "1825           2662        427        58          264.0       85.0       4.0   \n",
       "1837            229         48         4           26.0        3.0       1.0   \n",
       "1824           2874        209        49          123.0       30.0       4.0   \n",
       "1826           1431        104        23          321.0       24.0       2.0   \n",
       "1792            145         38         2            7.0        2.0       0.0   \n",
       "1832            810         72        11           26.0       10.0       3.0   \n",
       "1834            534         85         7            9.0        9.0       1.0   \n",
       "1827           1160         62        14           31.0        6.0       2.0   \n",
       "1828           1101         66        13           13.0        6.0       1.0   \n",
       "2220            101         27         1            2.0        1.0       0.0   \n",
       "1831            911        115         9           37.0       14.0       3.0   \n",
       "1851            103         23         1            1.0        8.0       0.0   \n",
       "1996            131         42         1            6.0        1.0       0.0   \n",
       "2107            148         42         1            2.0        0.0       0.0   \n",
       "2187            159         15         1            9.0        0.0       1.0   \n",
       "1966            161         28         1            4.0        0.0       0.0   \n",
       "1833            562         81         1           26.0        2.0       0.0   \n",
       "1925            391         94         0            5.0       12.0       0.0   \n",
       "2261            114         17         0            4.0        2.0       0.0   \n",
       "2106            228         63         0            5.0        7.0       0.0   \n",
       "1967            142         23         0            4.0        6.0       0.0   \n",
       "1926            327         78         0            4.0        7.0       0.0   \n",
       "1841            153         35         0            0.0       10.0       0.0   \n",
       "2095            119         17         0            3.0        2.0       0.0   \n",
       "1842            162         63         0            3.0       -4.0       0.0   \n",
       "2094            210         61         0            6.0        8.0       0.0   \n",
       "2097            121         28         0            4.0        2.0       0.0   \n",
       "1791            240         49         0            9.0       11.0       0.0   \n",
       "1794            141         54         0            4.0        7.0       0.0   \n",
       "1793            134         42         0            6.0       11.0       0.0   \n",
       "1843            144         49         0            1.0        3.0       0.0   \n",
       "1840            490        140         0            9.0       20.0       0.0   \n",
       "2096            109         14         0            4.0        0.0       0.0   \n",
       "\n",
       "                 update_time  fatality_rate  \n",
       "1835 2020-02-13 22:12:44.102       0.033333  \n",
       "1823 2020-02-13 22:12:44.102       0.031400  \n",
       "1829 2020-02-13 22:12:44.102       0.028169  \n",
       "1836 2020-02-13 22:12:44.102       0.027624  \n",
       "1965 2020-02-13 21:29:32.534       0.027397  \n",
       "1830 2020-02-13 22:12:44.102       0.025890  \n",
       "1825 2020-02-13 22:12:44.102       0.021788  \n",
       "1837 2020-02-13 22:12:44.102       0.017467  \n",
       "1824 2020-02-13 22:12:44.102       0.017049  \n",
       "1826 2020-02-13 22:12:44.102       0.016073  \n",
       "1792 2020-02-13 22:47:24.225       0.013793  \n",
       "1832 2020-02-13 22:12:44.102       0.013580  \n",
       "1834 2020-02-13 22:12:44.102       0.013109  \n",
       "1827 2020-02-13 22:12:44.102       0.012069  \n",
       "1828 2020-02-13 22:12:44.102       0.011807  \n",
       "2220 2020-02-13 20:39:00.939       0.009901  \n",
       "1831 2020-02-13 22:12:44.102       0.009879  \n",
       "1851 2020-02-13 22:12:44.102       0.009709  \n",
       "1996 2020-02-13 21:29:32.534       0.007634  \n",
       "2107 2020-02-13 20:39:00.939       0.006757  \n",
       "2187 2020-02-13 20:39:00.939       0.006289  \n",
       "1966 2020-02-13 21:29:32.534       0.006211  \n",
       "1833 2020-02-13 22:12:44.102       0.001779  \n",
       "1925 2020-02-13 21:29:32.534       0.000000  \n",
       "2261 2020-02-13 20:39:00.939       0.000000  \n",
       "2106 2020-02-13 20:39:00.939       0.000000  \n",
       "1967 2020-02-13 21:29:32.534       0.000000  \n",
       "1926 2020-02-13 21:29:32.534       0.000000  \n",
       "1841 2020-02-13 22:12:44.102       0.000000  \n",
       "2095 2020-02-13 20:39:00.939       0.000000  \n",
       "1842 2020-02-13 22:12:44.102       0.000000  \n",
       "2094 2020-02-13 20:39:00.939       0.000000  \n",
       "2097 2020-02-13 20:39:00.939       0.000000  \n",
       "1791 2020-02-13 22:47:24.225       0.000000  \n",
       "1794 2020-02-13 22:47:24.225       0.000000  \n",
       "1793 2020-02-13 22:47:24.225       0.000000  \n",
       "1843 2020-02-13 22:12:44.102       0.000000  \n",
       "1840 2020-02-13 22:12:44.102       0.000000  \n",
       "2096 2020-02-13 20:39:00.939       0.000000  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub_frm.sort_values('fatality_rate', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>update_date</th>\n",
       "      <th>province_name</th>\n",
       "      <th>province_name_en</th>\n",
       "      <th>city_name</th>\n",
       "      <th>city_name_en</th>\n",
       "      <th>cum_confirmed</th>\n",
       "      <th>cum_cured</th>\n",
       "      <th>cum_dead</th>\n",
       "      <th>new_confirmed</th>\n",
       "      <th>new_cured</th>\n",
       "      <th>new_dead</th>\n",
       "      <th>update_time</th>\n",
       "      <th>fatality_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1823</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>武汉</td>\n",
       "      <td>Wuhan</td>\n",
       "      <td>32994</td>\n",
       "      <td>1923</td>\n",
       "      <td>1036</td>\n",
       "      <td>13436.0</td>\n",
       "      <td>543.0</td>\n",
       "      <td>216.0</td>\n",
       "      <td>2020-02-13 22:12:44.102</td>\n",
       "      <td>0.0314</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     update_date province_name province_name_en city_name city_name_en  \\\n",
       "1823  2020-02-13           湖北省            Hubei        武汉        Wuhan   \n",
       "\n",
       "      cum_confirmed  cum_cured  cum_dead  new_confirmed  new_cured  new_dead  \\\n",
       "1823          32994       1923      1036        13436.0      543.0     216.0   \n",
       "\n",
       "                 update_time  fatality_rate  \n",
       "1823 2020-02-13 22:12:44.102         0.0314  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub_frm[sub_frm['city_name'] == '武汉']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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